CN1662940A - Area dividing system - Google Patents

Abstract

A region where a plurality of vending machines are installed is divided into charge-taken areas so that each operator may efficiently go round the area. A plurality of initial setting sections (114) are set such that an area including at least one vending machine is used as an initial value. A divisional processing section (115) calculates statistics determined by the characteristics of the vending machines included in each area, and the plurality of vending machine are reverted to some of the areas so that the difference in statistic in each area may be small.

Description

area division system

technical field

The present invention relates to a system that divides an area where a plurality of automatic vending machines are installed into areas in charge of operators engaged in automatic vending machine tour management.

Background technique

For example, a worker who uses a vending machine to sell products such as a bottling machine must regularly perform work such as product replenishment, inventory confirmation, cash collection, change replenishment, and garbage collection for each vending machine. At present, when a plurality of operators share the tour management of the vending machines in one business area, the area of each responsible area is manually divided approximately equally using a map. In this way, by performing division using a map, it is possible to visually grasp the state of the area division.

In addition, in order to improve the efficiency of each operator's tour management, it is proposed to try to use computers and networks to improve the efficiency of tour management of automatic vending machines. For example, it has been proposed to reduce the workload of an operator who replenishes a vending machine by grasping the stock situation of each vending machine in advance with a delivery vehicle (see Patent Document 1). As another example, a method has been proposed to equip automatic vending machines with a communication function, collect sales performance information from each automatic vending machine through the network, and formulate tour and supplementary plans based on the sales performance information, thereby improving the efficiency of tour management for each operator. (Refer to Patent Document 2).

Patent Document 1: Japanese Unexamined Patent Publication No. 9-204561

Patent Document 2: JP-A-2002-42217

However, even if the area of each area is roughly equally divided, the number of vending machines and various environmental conditions in each area are different, resulting in differences in the workload of tour management. In addition, in the process of manually dividing the area, due to the arbitrariness of the people responsible for dividing the work, the workload distribution lacks objectivity, which will create a sense of unfairness among the operators. In this way, up to now, the difference in environmental conditions of each area is still not considered, and the area is divided only by the area. Therefore, the workload of each operator cannot be grasped objectively.

In addition, the existing methods for improving the efficiency of tour management are only discussed from the perspective of how to tour the pre-allocated responsible areas as quickly as possible. Although the overall work efficiency can also be improved to a certain extent by improving the work efficiency of each operator, this method relies on the efforts of each operator, thus increasing the burden on the operator.

Contents of the invention

The object of the present invention is to provide a technique for dividing the area where a plurality of automatic vending machines are installed into a plurality of responsible areas in order to make the operator engaged in the automatic vending machine tour management feel fair and objective; another object of the present invention It is to provide a technology that divides the area where a plurality of vending machines are installed into a plurality of responsible areas in order to evenly distribute the workload of the operators who are engaged in vending machine touring work; another object of the present invention is to provide A technology that can objectively divide an area where a plurality of vending machines are installed into areas in charge of operators engaged in vending machine tour management while visually grasping the division state; another object of the present invention is to To provide a technique for dividing an area where a plurality of vending machines are installed into a plurality of responsible areas in order to improve the touring work efficiency of operators engaged in vending machine tour management; another purpose of the present invention is to provide a method for It is a technology that can reduce the total workload of all operators engaged in vending machine tours and divide the area where a plurality of vending machines are installed into a plurality of responsible areas.

The present invention provides an area division system that divides an area where a plurality of automatic vending machines are installed into areas in charge of operators engaged in tour management of automatic vending machines, wherein: , setting a plurality of areas including at least one vending machine in the area; the calculation part, which calculates the statistics determined according to the characteristics of the vending machines included in each area; the processing part, which selects the After specifying the area, the process of adding vending machines in the specified area to expand the area is repeated, and when the predetermined condition is satisfied, the process is stopped, and the obtained area is designated as the area in charge of a plurality of persons in charge.

Here, the characteristics of vending machines include location information of vending machines, configuration information between vending machines, operating time, sales amount, type of sales, moving speed and time between vending machines, from base, etc. The movement speed and movement time of the specified location, etc. In addition, the statistic can be calculated from the characteristics of all the vending machines included in the area, or can be calculated from the characteristics of the vending machines showing specific properties compared with other vending machines. Here, the predetermined condition may be, for example, when all the vending machines in the area belong to any one area, when a predetermined number of candidate selection processes are performed, and when the statistical difference between areas is within a predetermined range. , or when the conditions formed by an appropriate combination of the above-mentioned conditions are satisfied.

By repeating the process of expanding the area in this way, the target area can be objectively divided into areas based on predetermined criteria.

The area division system of the present invention can further include a candidate selection unit that selects a candidate automatic vending machine to be added for each area. The calculation unit calculates the statistical amount when the candidate vending machine is added for each area, and the processing unit can select a specific area in consideration of the statistical amount when the candidate automatic vending machine is added.

In the area division system of the present invention, the processing unit can select a specific area in a state where a vending machine is added in any area, and reduce the difference in statistics of each area.

In the area division system of the present invention, the processing unit evaluates the uniformity of the statistics of each area when the vending machine is added in any area, and can select a specific area based on the evaluation result.

In the area division system of the present invention, the processing unit can select a specific area so that the differences in the statistics of each area are the most equal when the automatic vending machine is installed in any area. In this way, the statistics can be evenly assigned to a certain area, and the target area can be divided fairly.

In the area classification system of the present invention, the processing unit can change the area where the vending machine is to be added, evaluate the equality of statistical quantities in various cases, and select a specific area by comparing the equalities.

The area division system of the present invention may further include a position information storage unit storing position information of the automatic vending machine, and the candidate selection unit may select candidates by referring to the position information of the automatic vending machine.

In the area division system of the present invention, the candidate selection unit can sequentially select based on the position information of the vending machines assigned to each person in charge and in consideration of the distance from the representative point to be specified. Since the present invention selects a candidate vending machine in consideration of the distance from the representative point of the area, the target area can be appropriately divided into areas of a predetermined shape.

In the area dividing system of the present invention, the candidate selection unit can specify a representative point based on the position information of all the automatic vending machines assigned to each person in charge.

In the area division system of the present invention, the candidate selection unit can specify the center of gravity of the positions of the automatic vending machines assigned to each person in charge as a representative point.

In the area division system of the present invention, the statistics can be used as the workload when each person in charge tours and operates the vending machines included in each area in charge. According to the present invention, since the area division is performed in consideration of the workload of each person in charge, for example, the workload of each person in charge can be evenly divided into the area of interest and the target area can be divided fairly.

In the area division system of the present invention, the calculation unit can calculate the statistics in consideration of the travel time between the vending machines.

The area classification system of the present invention can further include a characteristic information storage unit that stores information on characteristics of each automatic vending machine.

In the area dividing system of the present invention, the characteristic information storage unit can store the position information of each vending machine, and the calculation unit can calculate the travel time between the vending machines based on the position information between the vending machines.

In the area division system of the present invention, the area can include bases, and the calculation unit can calculate the statistics in consideration of the travel time between the bases and each automatic vending machine. The area division system of the present invention can further include a base information storage unit that stores positional information of bases.

In the area classification system of the present invention, the calculation unit can calculate the statistical quantity in consideration of the operation time of each automatic vending machine.

In the area classification system of the present invention, the calculation unit can calculate the statistical quantity based on the type of each automatic vending machine.

In the area division system of the present invention, the processing unit can add automatic vending machines in each responsible area so that the distance between the automatic vending machines included in each responsible area is within a predetermined limit distance. In this way, relatively close vending machines whose mutual distances are within a predetermined range are classified into the same area, so that the target area can be divided into areas. In addition, it is possible to shorten the working time in each area when going around and operating between vending machines.

The area division system of the present invention may further include a weight value setting unit that adds a weight value to the statistical quantity for each area, and the calculation unit may calculate the statistical quantity in consideration of the weighted value.

The area dividing system of the present invention may further include a combination designation receiving unit that receives a combination designation of an automatic vending machine to be included in the same area in charge among a plurality of automatic vending machines. The initial setting unit or the processing unit can include the automatic vending machines of the specified combination in the same area in charge.

The area dividing system of the present invention can further have a map information storage unit storing map information of the area and a display processing unit, and the display processing unit displays the automatic vending machines included in each responsible area together with the map information to indicate that each responsible area regional differences.

The area classification system of the present invention may further include a property information receiving unit that receives input of information on properties of the automatic vending machine via a network.

The present invention provides a data structure used when dividing an area where a plurality of automatic vending machines are installed into areas in charge of operators who perform automatic vending machine tour management, including: a first data section, which is assigned to each area, which distinguishes and stores the identification information of the vending machines that have already belonged to each responsible area and the identification information of the candidate vending machines that will belong to each responsible area; It is a statistic calculated by information on the characteristics of the vending machines in each area in charge and the characteristics of the vending machines that are candidates to be assigned to each area in charge. In this way, it is possible to discriminate between the automatic vending machines already assigned to each responsible area and the candidate automatic vending machines to be assigned to each responsible area, and it is also possible to combine these automatic vending machines and calculate statistics.

The data structure of the present invention may further include a data unit that performs statistics determined by the characteristics of the automatic vending machines already assigned to each responsible area and the automatic vending machines that will be assigned to each responsible area as candidates for each responsible area. storage.

In the data structure of the present invention, the information on the characteristics of the above-mentioned automatic vending machines includes the position information of each automatic vending machine, and the above-mentioned data structure can further include a data part that puts the information based on the position of the automatic vending machines that have been assigned to each responsible area. The positional information of the representative spot specified by the information is stored for each responsible area.

The data structure of the present invention may further include a data part for marking a corresponding responsible area when the identification information of the automatic vending machine stored in the first data part changes.

Description of drawings

The above objects and other objects, features, and advantages will be further clarified by the following embodiments and accompanying drawings.

FIG. 1 is a flow chart showing the region division processing sequence of the first embodiment of the present invention;

Fig. 2 is a schematic diagram showing the sequence shown in Fig. 1;

3 is a block diagram showing the structure of an area simulation device for performing area division processing according to the first embodiment of the present invention;

Fig. 4 is a diagram showing a part of the data structure of the vending machine information storage unit shown in Fig. 3;

Fig. 5 is a block diagram showing in detail the initial setting unit shown in Fig. 3;

FIG. 6 is a diagram showing a part of the data structure of the initial setting storage unit shown in FIG. 3;

Fig. 7 is a block diagram showing in detail the division control unit shown in Fig. 3;

Fig. 8 is a block diagram showing in detail the logic storage unit shown in Fig. 3;

FIG. 9 is a diagram showing a part of the data structure of the area division information storage unit shown in FIG. 3;

FIG. 10 is a flow chart showing the procedure for setting a seed point according to the first embodiment of the present invention;

FIG. 11 is a diagram illustrating an example of a seed point setting process shown in FIG. 10;

FIG. 12 is a diagram illustrating another example of the seed point setting process shown in FIG. 10;

FIG. 13 is a flow chart showing the sequence of region division processing according to the embodiment of the present invention;

Fig. 14 is a flow chart showing the sequence of selecting the candidate self-vending machine in step 102 shown in Fig. 13;

FIG. 15 is a diagram illustrating an example of the area division processing shown in FIGS. 13 and 14;

FIG. 16 is a flowchart showing the calculation processing procedure of the total number of routes in each divided area;

FIG. 17 is a diagram showing a part of the data structure of an area division information storage unit;

FIG. 18 is a diagram showing a screen for parameter setting and initial setting;

FIG. 19 is a diagram showing a screen for parameter setting and initial setting;

FIG. 20 is a diagram showing a screen for parameter setting and initial setting;

FIG. 21 is a diagram showing a screen for parameter setting and initial setting;

FIG. 22 is a diagram showing a screen for parameter setting and initial setting;

FIG. 23 is a diagram showing a screen for parameter setting and initial setting;

FIG. 24 is a flowchart showing the processing procedure when the adjustment accepting unit accepts replacement processing from the user;

25 is a flowchart showing the sequence of seed point setting processing and region division processing in the second embodiment of the present invention;

26 is a diagram showing a setting screen of candidate seed points and selection conditions in the second embodiment of the present invention;

Fig. 27 is a block diagram showing the structure of an area simulation device according to a third embodiment of the present invention;

Fig. 28 is a block diagram showing in detail the initialization unit shown in Fig. 27;

Fig. 29 is a block diagram showing in detail the logic storage unit shown in Fig. 27;

30 is a flowchart showing the sequence of seed point setting processing and region division processing in the third embodiment of the present invention;

FIG. 31 is a flowchart showing the procedure of area number calculation processing in step 222 shown in FIG. 30;

FIG. 32 is a diagram showing a screen for parameter setting and initial setting;

FIG. 33 is a diagram showing a screen for parameter setting and initial setting;

FIG. 34 is a diagram showing a screen for parameter setting and initial setting;

35 is a diagram showing an area simulation system including an area simulation device according to a fifth embodiment of the present invention;

Fig. 36 is a diagram showing another example of a part of the data structure of the vending machine information storage unit;

Fig. 37 is a diagram showing another example of a part of the data structure of the vending machine information storage unit;

Fig. 38 is a block diagram showing the structure of the area simulation device of the first embodiment having a data registration receiving unit;

Figure 39 shows a screen for registering the vending machine information data;

Fig. 40 shows a screen for registering vending machine information data.

Detailed ways

In the embodiment of the present invention, an example will be described by dividing a business area with a plurality of automatic vending machines (hereinafter referred to as "vending machines") into responsible areas for operators who are engaged in the tour management of the vending machines. Here, when a plurality of operators share the tour operation of the vending machines included in the divided business area, area division is performed to improve the overall work efficiency and equally distribute the workload of each operator. In addition, each operator is stipulated to carry out the following tour work, that is, starting from the business office and other bases every day, patrolling the vending machines in the area he is in charge of, performing operations such as product replenishment and delivery, and returning to the base at the end of the day's work. Therefore, in order to improve the overall work efficiency, it is better to make the distances between the bases of the operators-the vending machines and the vending machines-the vending machines relatively close when performing area division. In addition, in order to equally distribute the workload of each operator, it is better to divide the area while adjusting the workload of the tour work in a plurality of areas.

(Example 1)

FIG. 1 is a flowchart showing the procedure of area division processing in the first embodiment of the present invention. Firstly, the registration of various data necessary in the area division process is carried out (S1), and then the parameter setting necessary for the area division is performed (S2), and then the number of areas set in the business area is set (S3) and used as each Initial settings such as setting of the seed point of the starting point of the region (S4), and then perform region division with the seed point as the starting point (S5), and then display the result of the region division, and perform evaluation and adjustment (S6).

Fig. 2 is a schematic diagram showing the sequence shown in Fig. 1 .

Before performing the area division process, registration of various data such as map information data, base information data, and vending machine information data is performed. Then, based on the registered various data, map information is drawn on the screen, and bases and vending machine points are marked on the corresponding positions of the map information. In addition, parameter settings and initial settings necessary for area division are performed. Based on the parameters and initial settings, the business area is divided into regions by the region division engine. Then, the map information and the area division state image are displayed on the screen, and at the same time, the list of statistics of each area is displayed. The so-called statistics here refer to information indicating the characteristics of the vending machines included in each area, for example: the number of routes (daily workload) in each area, the number of vending machines included in each area, and the number of vending machines included in each area. The average loading operation time of vending machines, the average monthly loading times of each vending machine, the average distance from the base to each vending machine, the average distance between vending machines, the number of vending machines on each route , total sales, average sales per vending machine, etc. The user can see the displayed divided areas and statistics on the screen (not shown), and can confirm the divided state of the areas. Based on the statistics of each area, the parameters can be reset manually or automatically according to the needs, and the area division can be performed again. In addition, based on the displayed information, the user can manually perform an operation to change the positioning point of the vending machines belonging to each area. Through the above processing, area division data is created and stored.

FIG. 3 is a block diagram showing the configuration of an area simulation device that performs area division processing in this embodiment. The area simulation device 100 has a display processing unit 108, a parameter setting unit 110, an initial setting unit 114, a division processing unit 115, a map information storage unit T1, a base information storage unit T2, a vending machine information storage unit T3, and a parameter storage unit. T4, an initial setting storage unit T5, an area division information storage unit T6, and a logical storage unit T7. The division processing unit 115 has a candidate selection processing unit 116 and a division control unit 118 .

The map information storage unit _T1 stores map information data of business districts to be classified. The base information storage unit _T2 stores base information data. The base information data includes a base identification code, a base name, a base location (latitude and longitude or x coordinate and y coordinate) and the like. The so-called base here is, for example, a business office in the business area.

The vending machine information storage unit _T3 stores vending machine information data. Self-vending machine information data includes base identification code, self-vending machine identification code, self-vending machine name, self-vending machine location (latitude, longitude, height or x, y, z coordinates), monthly turnover (Japanese yen), monthly Loading amount (unit), each loading operation time (minutes), monthly loading times, moving speed from base (km/hour), moving speed between vending machines (km/hour), etc. FIG. 4 is a diagram showing a part of the data structure of the vending machine information storage unit T3 of this embodiment. Here, for example, the vending machine with the vending machine code "a" belongs to the base with the base code "1000", the name is "supermarket", the location is "(X ₁ , Y ₁ )", and the height is "above ground" , the operating time on the vending machine is "25 minutes".

Returning to FIG. 3 , the display processing unit 108 performs processing for displaying various data on a screen (not shown). The parameter setting unit 110 accepts the setting of parameters necessary for classifying business areas. The parameters include the standard working time of each operator in a day, the standard operating time of the respective vending machines, the standard moving speed between the vending machines, the standard moving speed between the stronghold and the vending machines, the distance multiplier, the vending machine acquisition limit distance etc. The parameter storage unit _T4 stores the above-mentioned parameters.

The initialization unit 114 performs initialization necessary for dividing the business area into areas. The initial setting unit 114 receives a user's instruction for selection of a seed point setting method, setting of the number of regions, weighting value setting, combination designation, and the like. FIG. 5 is a block diagram showing in detail the initialization unit 114 shown in FIG. 3 . The initial setting unit 114 has a seed point setting unit 122 , a combination designation receiving unit 132 , a weighting value setting receiving unit 134 , and an end condition setting receiving unit 135 . The seed point setting unit 122 has a seed point setting method receiving unit 124 , a seed point setting receiving unit 126 , an area number setting receiving unit 128 , and a seed point selecting unit 130 .

Here, the seed point refers to a vending machine that is the starting point of each area when the area is divided. In this embodiment, for example, when dividing the business area to be divided into four blocks, four seed points are set. The seed point setting unit 122 selects a vending machine as a seed point from a plurality of vending machines. The seed point setting method receiving unit 124 receives a selection of manual or automatic as the seed point setting method. When the seed point setting method receiving unit 124 receives a manual seed point setting method, the seed point setting receiving unit 126 receives an input of setting a seed point from the user. In addition, when the seed point setting method receiving unit 124 receives the automatic seed point setting method, the region number setting receiving unit 128 receives setting of the region number from the user. The seed point selection unit 130 automatically selects the number of seed points set in the region number setting reception unit 128 . There are many ways to automatically set the seed point, but the seed point is set so that when the vending machines in the business area are classified starting from various sub-points, the business area is divided into regions.

The combination designation receiving unit 132 receives designation of a combination of vending machines divided into the same area among a plurality of vending machines from the user. The user can designate a combination by referring to the points of the vending machines drawn on the screen, or can designate a combination by referring to the vending machine information storage unit T3.

The weighted value setting reception unit 134 receives the weighted value setting to be added to the statistics when calculating the statistics of a plurality of regions set with the seed points set by the seed setting unit 122 as respective starting points.

The end condition setting receiving unit 135 receives setting of a condition for ending the area division process. As an end condition, for example, it may be: (i) when all the vending machines belong to a certain area; (ii) when the process of obtaining the vending machines in one area is performed a predetermined number of times; (iii) the statistics of each area When the difference is within the specified range; or when the conditions for an appropriate combination of (i) to (iii) are satisfied.

Returning to FIG. 3 , the initial setting storage unit T5 stores these initial settings. FIG. 6 is a diagram showing a part of the data structure of the initial setting storage unit T5. Here, for example, it is assumed that vending machines with vending machine codes "a" to "z" are installed in the business area to be classified. Here, the vending machine with the vending machine code "a" is selected as the seed point in area 1, and the vending machine with the vending machine code "e" is selected as the seed point in area 2. In addition, the weight value "1" is added to the area 1, and the weight value "2" is added to the area 2. In addition, the vending machine with the vending machine code "c" and the vending machine with the vending machine code "d" are specified in combination. Thus, when any one of the vending machine with the vending machine code "c" and the vending machine with the vending machine code "d" is acquired by a certain area, the vending machine with the vending machine code "c" The other one of the vending machine and the vending machine code "d" is also taken by the area at the same time.

Returning to FIG. 3 , the division processing unit 115 performs area division of the division target business area starting from the various sub-points set in the initialization unit 114 . The candidate selection processing unit 116 selects, for each area, a vending machine that is close to the representative point of the area as a candidate to be classified into the area. The division control unit 118 assigns the corresponding vending machine candidates to a certain area, and makes the statistics of each area most equal among the areas. As shown in FIG. 7 , the division control unit 118 includes a statistic calculation unit 136 , a candidate assignment processing unit 138 , and an adjustment reception unit 140 . The statistical amount calculation unit 136 calculates the statistical amount determined based on the vending machine meters included in each area. The candidate assignment processing unit 138 sequentially assigns a plurality of vending machines to each area, and makes the statistics of each area calculated by the statistics calculation unit 136 approximately equal in all areas. After the area division by the candidate selection processing unit 116 , the statistic calculation unit 136 , and the candidate attribution processing unit 138 , the adjustment receiving unit 140 receives adjustments such as replacement of vending machines belonging to each area from the user. When the adjustment receiving unit 140 receives an adjustment from the user, the statistic calculation unit 136 calculates the statistic of each area when the adjustment is performed, and as a result, if the amount of change produced by the adjustment is within the allowable range, the adjustment receiving unit 140 allows the adjustment. .

As shown in FIG. 8 , the logical storage unit T7 includes a logical storage unit T7 a for seed point selection, a logical storage unit T7 b for candidate selection, and a logical storage unit T7 c for statistic calculation. The logic storage part T7a for seed point selection stores the logic necessary for automatic seed point setting in the seed point selection part 130. The candidate selection logic storage unit T7b stores logic necessary for selecting candidate points belonging to each area in the candidate selection processing unit 116 . The statistic calculation logic storage unit T7 c stores logic necessary for calculating the statistic in the statistic calculation unit 136 of the division control unit 118 .

When the automatic area division processing by the division processing unit 115 is completed, the result is stored in the area division information storage unit T6. FIG. 9 is a diagram showing a part of the data structure of the area division information storage unit T6. Here, the business area is divided into four areas of area 1 to area 4 . For example, the vending machines with codes "a" and "b" belong to area 1. Similarly, the vending machines with codes "d", "u" and "z" belong to area 2, 3, 4. The area classification information storage unit T6 can store various data calculated based on the vending machine information of the vending machines belonging to each area for each area, for example, the average travel time M ₁ between the storage base and the vending machine, the vending machine The average moving time M ₂ between them, the number N ₂ of vending machines that must be processed, statistics (total number of routes), etc. The calculation method of these data will be described later.

In addition, the display processing unit 108 displays the area division state on a screen (not shown). In this way, the user can grasp the area division state, and the user can perform adjustments such as parameter setting again, initial setting change, or replacement of vending machines belonging to each area based on the displayed area division state.

FIG. 10 is a flowchart showing the logic necessary for the seed point selection unit 130 to automatically set the seed point, which is stored in the seed point selection logic storage unit 7a in this embodiment.

The area number setting receiving part 128 receives the area number (seed point number) setting from the user (S10), and then the seed point selection part 130 selects any one of the area number from the points corresponding to a plurality of vending machines in the business area. point as the initial point (S12). In addition, the initial points can be selected in order in the table with reference to the vending machine information storage unit T3. The seed selection part 130 detects the shortest distance _I1 (S14) between the selected initial points, then, the seed point selection part 130 selects the next self-vending machine in the table of the self-vending machine information storage part T3 as a check point (S16 ), and calculate the shortest distance I ₂ between the initial point closest to the checkpoint and the checkpoint among the initial points (S18). Then, the seed point selection unit 130 performs a first check (S20). In the first check, the shortest distance I ₁ between the initial points detected in step 14 is compared with the shortest distance I ₂ calculated in step 18 ( S22). When the shortest distance _I2 is greater than the shortest distance _I1 (YES in S22), the seed point selection unit 130 replaces any one of the check point and the initial point as a new selected point (S24). Here, the point to be replaced is the initial point closest to the check point among the points constituting the shortest distance _I1 between the initial points.

In step 22, when the shortest distance I ₂ is below the shortest distance I ₁ (No in S22), the seed point selection unit 130 calculates the shortest distance I ₃ from the check point to an initial point other than the nearest initial point (S26 ), and calculate the shortest distance I ₄ from the nearest initial point to other initial points (S28), and then perform the second check (S30). In the second check, the seed point selection unit 130 compares the shortest distance I ₄ between the nearest initial point and other initial points with the shortest distance I ₃ calculated in step 26 ( S32 ). When the shortest distance I ₃ is large (Yes in S32 ), proceed to step 24, and the seed point selection unit 130 replaces the inspection point with the nearest initial point as a new selected point (S24).

In step 32, when the shortest distance I ₃ is smaller than the shortest distance I ₄ between the nearest initial point and other initial points (No in S32), no point replacement is performed.

The above processing is performed a predetermined number of times for all points in the business area, for example, 100 times here. In step 34, when i is below 100 (S34 is No), return to step 14, select the shortest distance I ₁ between the new selection points, and the seed point selection part 130 selects from the table of the vending machine information storage part T3 The next vending machine is used as a check point (S16), and the same process is repeated hereafter. On the other hand, in step 34, when i>100 (YES in S34), the point selection process ends. The seed point selection unit 130 selects the selected point at this stage as a seed point.

FIG. 11 is a specific explanatory diagram of the seed point setting process described with reference to FIG. 10 . Here, the number of regions is set to 3. First, as shown in Figure 11(a), point a, point b, and point c are selected as initial points. The seed point selection unit 130 detects the shortest distance between these initial points. Here, the distance between point a and point b is the shortest distance L ₁ , and then point d is selected as the check point. The seed point selection unit 130 detects the initial point closest to point d, and calculates the shortest distance between point d and the nearest initial point, where the distance between point d and point c is the shortest distance L ₂ . The seed point selection unit 130 compares the shortest distances L ₁ and L ₂ . In this embodiment, because the shortest distance L ₂ >shortest distance L ₁ , the seed point selection unit 130 replaces point d with other initial points as a new selection point . Here, the point to be replaced with point d is one of point a or point b constituting the shortest distance _L1 . As shown in FIG. 11( b ), the seed point selection unit 130 calculates the distances L ₃ , L ₄ between the point d and the replacement points a and b in order to determine a replacement point to be replaced with the point d. Here, since L ₄ >L ₃ , the point a becomes the replacement object. As shown in FIG. 11( c ), through the above processing, point b, point c, and point d become new selection points. The same process is repeated, and the selection point at which a predetermined number of processes has been completed is selected as a seed point.

FIG. 12 is a diagram illustrating another example of seed point setting processing. Here too, the number of regions is set to three. First, as shown in Figure 11(a), point a, point b, and point c are selected as initial points. The seed point selection unit 130 detects the shortest distance between these initial points, where the shortest distance L ₁ is between point a and point b. Then, select point e as a checkpoint. The seed point selection unit 130 detects the initial point closest to the point e, and calculates the shortest distance between the point e and the nearest initial point. Here, the shortest distance L ₂ is between point e and point b. The seed point selection unit 130 compares the shortest distance L ₁ and the shortest distance L ₂ . In this embodiment, since the shortest distance L ₂ <shortest distance L ₁ , the seed point selection unit 130 performs the second check.

As shown in FIG. 11( b ), the seed point selection section 130 calculates the shortest distance L ₃ between the point a and the point e next to the point e other than the initial point b closest to the point e as the check point, and , also calculate the shortest distance L ₁ between the nearest point b and the closest point a. The seed point selection unit 130 compares the shortest distance L ₃ and the shortest distance L ₁ . In this embodiment, since the shortest distance L ₃ >shortest distance L ₁ , point e is replaced with the nearest point b. Through the above processing, as shown in FIG. 11( c ), point a, point c, and point e become new selection points. The same processing is repeated, and the selection point selected when the predetermined number of processing is completed is set as a seed point.

In the above processing, in the first check, since the selection point is replaced when the shortest distance between the existing selection point and the check point is longer than the shortest distance between the existing selection points, the distance between the points Combinations of points with short distances will be excluded. In addition, among the selected points to be replaced, the selected points whose distance to the inspection point is short are replaced, so that the distance between new selected points can be further increased. In addition, even if the conditions of the first inspection cannot be satisfied, in the second inspection, in the case of replacing the existing selection point and inspection point, the point replacement can be performed when the distance from other selection points is further increased . Therefore, displace the selected points so that the distance between the points is longer. Through the above processing, among the plurality of vending machines, the vending machines whose mutual distances are equally extended can be set as seed points.

FIG. 13 is a flowchart showing the procedure of area division processing performed by the area simulation device 100 in this embodiment. First, the initial setting unit 114 manually or automatically sets seed points (S102), and the candidate selection processing unit 116 selects candidate vending machines belonging to the same area for each sub-point (S104).

Here, the procedure in which the candidate selection processing unit 116 selects a candidate vending machine belonging to each area in step 104 will be described with reference to FIG. 14 . FIG. 14 is a flowchart showing the logic necessary for the candidate selection processing unit 116 to select a candidate, which is stored in the candidate selection logic storage unit T7b in this embodiment. Since the candidate selection processing unit 116 performs the same processing for each area, only one area will be described. First, the candidate selection processing unit 116 calculates the position of the representative point of each area. Here, the candidate selection processing unit 116 calculates the center of gravity of the vending machine acquired in the area as the representative point (S130). In the stage where only seed points are included in each area, the location of the vending machine at the seed point is used as the center of gravity.

Next, the candidate selection processing unit 116 detects the vending machine closest to the representative point of the area from the unaffiliated vending machines that do not yet belong to any area as a temporary candidate (S132). Next, the shortest distance between the vending machine that is closest to the vending machine detected as temporary replenishment and the temporary replenishment vending machine among the vending machines already assigned to the area is calculated ( S134 ). The calculated shortest distance is compared with the limit distance for obtaining the self-vending machine preset by the parameter setting unit 110 (S136), and when the shortest distance is within the limit (S136 is Yes), it is determined to use the temporary supplementary self-service machine. The vending machine is used as a candidate for this area (S138). When a new candidate is determined in one area, the candidate selection processing unit 116 raises a small flag in the area. On the other hand, in step 136, when the shortest distance exceeds the limit (S136 is No), it is judged whether there are other vending machines without belonging (S140). When there are other unowned self-vending machines (S140 is yes), return to step 132, detect the next self-vending machine on the shortest position apart from the distance of the area representative point, as a temporary supplement, below, repeat the same process .

In step 140, when there are no other unaffiliated vending machines (No in S140), the representative point of the distance area is detected from all the vending machines including the obtained vending machines already acquired by other areas. The nearest self-vending machine is used as a temporary supplement (S142). And the shortest distance between the vending machine which is closest to the vending machine detected as a temporary replacement among the vending machines already assigned to the area and the temporary replacement vending machine is calculated (S144). Then, the calculated shortest distance is compared with the limit distance for obtaining the vending machine preset by the parameter setting unit 110 (S146), and when the shortest distance is within the limit (S146 is Yes), it is determined to use the temporary The candidate vending machines are candidates for the area (S138). On the other hand, in step 146, when the shortest distance exceeds the limit (S146 is no), it is judged whether there are other self-vending machines that can be seized (S148) in the self-vending machines that have been obtained. In the case of a vending machine (YES in S148), the process returns to step 142, and the next vending machine located at the shortest distance from the representative point of the area is detected as a candidate. Hereinafter, the same processing is repeated. In addition, in step 148, when there is no vending machine that can be seized (NO in S138), the process of selecting candidates for the area ends.

Returning to FIG. 13 , it is judged whether a candidate is selected in step 104 ( S106 ), and the statistic calculation unit 136 judges whether a candidate has been selected in step 104 based on whether a small flag is erected in each area. When a candidate is selected in step 104 (YES in S106), the statistic calculation unit 136 calculates the statistic of the area including the candidate vending machine (S108). As the statistic, for example, the total route number can be used, and the calculation method of the total route number will be described later.

Next, the candidate attribution processing unit 138 detects the region with the smallest statistic (S110), and when the candidate attribution processing unit 138 detects that the statistic is the smallest (S110: Yes), the candidate attribution processing unit 138 acquires the candidate for this region. A vending machine (S112). Next, the candidate belonging processing unit 138 refers to the initial setting storage unit T5, and judges whether or not the area dividing process satisfies the end condition (S114). As an end condition, it can be set, for example, that there is no longer any unaffiliated vending machine in the business area; the acquisition candidate processing in step 112 has been performed a predetermined number of times, for example, 100 times or more; and the difference in statistics in each area is within a predetermined range. Wait within. When the end condition is not satisfied (No in S114), the process returns to step 104, and the next candidate is selected. In step 114, when the end condition is satisfied (YES in S114), the area dividing process is ended.

In step 110, when it is detected that the statistic is not the minimum (No in S110), the process proceeds to step 116, and the candidate assignment processing unit 138 retains the processing of the area until obtaining candidates from other areas (No in S116). In step 116, when the candidate is acquired from another area (YES in S116), the candidate attribution processing unit 138 detects whether the vending machine already acquired in the area is seized by another area (S118). When not being seized (S118 is no), then explanation has no change in the vested vending machine and the candidate in this area, so return to step 110, can judge again whether statistic is minimum (S110).

In step 118, when the self-vending machines acquired in this area are captured by other areas (Yes in S118), go to step 114 to judge whether the end condition is satisfied. Here, when the end condition is not satisfied (No in S114), the process returns to step 104, and the candidate selection processing unit 116 performs a process of selecting a new candidate.

On the other hand, if the candidate is not selected in step 104 (No in S106), the process proceeds to step 120, and the candidate attribution processing unit 138 retains the processing of the area until the candidate is obtained from another area (No in S120). In step 120, when a candidate is acquired from another area (YES in S120), the candidate attribution processing unit 138 detects whether the vending machine already acquired in the area is seized by another (S122). When the self-vending machine obtained in this area is captured by other areas (S122 is yes), enter step 114, and judge whether to meet the end condition. Here, when the end condition is not satisfied (No in S114), the process returns to step 104, and the candidate selection processing unit 116 performs a process of selecting a new candidate.

In addition, in step 122, when the vending machines already acquired in this area are not seized by other areas (No in S122), proceed to step 124, and the candidate attribution processing unit 138 refers to the initial setting storage unit T5 to determine whether the area division processing satisfies the requirements. end condition. When it is judged in step 124 that the end condition is satisfied (YES in S124), the area dividing process ends. In addition, in step 124, when it is judged that the end condition is not satisfied (No in S124), the process returns to step 120, and the candidate attribution processing unit 138 reserves the processing of the area until obtaining candidates from other areas (No in S120). Hereinafter, the same processing is performed.

In addition, in the candidate selection process of step 104, the vending machine selected as a candidate for a certain area is processed as having no affiliation. In addition, when the candidate vending machines in a plurality of areas overlap, the area with a higher priority order of specifying "acquisition" acquires the vending machine.

FIG. 15 is a diagram illustrating an example of the area division processing shown in FIGS. 13 and 14 . Here, area division is performed to equalize the distribution of the total number of routes in each area. As shown in FIG. 15( a ), vending machines and bases corresponding to points a to z are installed in the business area. Hereinafter, a case where the number of regions is set to four by the initial setting unit 114 will be described.

As shown in FIG. 15( b ), the seed point setting unit 122 sets points a, d, u, and z as seed points of areas 1, 2, 3, and 4, respectively. The display processing unit 108 performs processing for displaying points belonging to different regions with different labels and different colors.

As shown in FIG. 15( c ), the candidate selection processing unit 116 selects candidate points belonging to regions 1, 2, 3, and 4, respectively. Here, the candidate selection processing unit 116 selects point e as a candidate for area 1 , point g as a candidate for area 2 , point q as a candidate for area 3 , and point y as a candidate for area 4 . The statistic calculation unit 136 gradually calculates the total number of routes in each area according to a calculation method described later. The candidate belonging processing unit 138 acquires candidates from the area with the smallest total number of routes, detects the area with the smallest total number of routes each time a certain area acquires candidates, and repeats the process of acquiring candidates.

When points are sequentially selected in each area in this way, as shown in FIG. 15( d ), a plurality of points gradually belong to each area.

Hereinafter, the process of selecting the next candidate point in the area 3 will be described with reference to FIG. 15( d ). As described in step 132 of FIG. 14 , the candidate selection processing unit 116 first detects a temporary candidate from points that do not belong, and the temporary candidate at this time is point o. The candidate selection processing unit 116 calculates the distance between the point s closest to the point o among the points already acquired in the area 3 and the point o, and compares the distance with a preset limit distance for obtaining vending machines. Here, the calculated distance is designed to be larger than the acquisition limit distance. In this case, the candidate selection processing unit 116 cannot select the point o as a candidate for the region 3 .

The candidate selection processing unit 116 sequentially detects temporary candidates in order of the distance from the center of gravity of the area 3 for the unaffiliated points. As a result, when the shortest distances between all the points and the points already assigned to area 3 are greater than the limit distance for acquiring vending machines, the candidate selection processing unit 116 includes the vending machines already acquired in other areas, and restarts Perform interim testing. As a result, the candidate selection processing unit 116 detects another point x already assigned to the area 4 as a temporary candidate, and calculates the distance between the point s closest to the point x among the points already acquired in the area 3 and the point x. The candidate selection processing unit 116 compares this distance with a preset limit distance for obtaining vending machines, and here, when the calculated distance is within the obtain limit distance, selects point x as a candidate for area 3 .

In addition, for the points captured from other areas in the upcoming processing, for example, set up a small flag to prevent them from being captured. If this is done, for example, point x was originally acquired by area 3, but when it is captured by area 4 immediately before this process, area 3 cannot capture point x from area 4 as the next candidate, thus, It is possible to prevent the problem of actually stopping the process of obtaining candidates by repeatedly performing capture of one point between two areas.

According to the area division processing of this embodiment, a vending machine at a position closer to a representative point such as the center of gravity of the area is selected as the next candidate, so that each area can be formed into a square shape. Accordingly, when dividing a plurality of vending machines in the business area into a plurality of groups while considering the statistics of the vending machines, these vending machines can be divided into regions without crossing regions. Therefore, it is easy to grasp the grouping state, and it is possible to make the operator feel fair.

FIG. 16 is a flowchart showing the logic stored in the statistic calculation logic storage unit T7c for the statistic calculation unit 136 to calculate the total number of routes in each area. Since the same processing is performed for each area, only one area will be described here. The statistic calculation unit 136 appropriately refers to the site information data stored in the site information storage unit T2, the vending machine information data stored in the vending machine information storage unit T3, and the parameters stored in the parameter storage unit T4 as follows: The total number of routes is calculated sequentially.

The statistic calculation unit 136 first calculates the average travel time M ₁ of moving from the base to the vending machine and the candidate vending machine already belonging to the area (S160). First find the total distance from the base to each vending machine, and then divide the total distance with the moving speed between the base and the vending machine set by the parameter setting part 110 to find the total travel time, and then use the area M ₁ is calculated by dividing the total time by all the vending machines in .

Next, the statistic calculation unit 136 calculates the average travel time M ₂ between vending machines (S162). First, the total distance from each vending machine to the nearby n vending machines is obtained, and then the total distance is divided by the moving speed between vending machines set by the parameter setting unit 110 to obtain the total travel time, Next, the total travel time is divided by n to obtain the average travel time m ₁ to m _n from each vending machine to another vending machine. Then, these average travel times m ₁ to m _n are summed up and divided by the number of all vending machines in each area to calculate M ₂ . Here, when the value of n is small, the number of all vending machines in the area can be taken as n.

Next, the statistic calculation unit 136 calculates the number N ₁ of vending machines that can be operated in one day (S164). The total operating time of a day is: T _Z =2×M ₁ +M ₂ ×(N ₁ -1)+T×N ₁ , (T is the average operating time of a vending machine), transform this formula and calculate N ₁ =(T _Z −2×M ₁ +M ₂ )/(M ₂ +T).

On the other hand, the statistic calculation unit 136 calculates the number N ₂ of vending machines that must be processed each day (S166). First, calculate the monthly filling times of each vending machine, and sum up the monthly filling times of the respective vending machines, thereby calculating the monthly filling times W. Next, the number of working days of each operator in one month is calculated as: 5 days x 4 (weeks) = 20 days/month, and N ₂ =W/20 is obtained.

Then, the statistic calculation unit 136 divides the number N ₂ of self-vending machines that need to be processed each day by the number N ₁ of self-service vending machines that can be operated in a day, thereby calculating the number of routes in each area = N ₂ /N ₁ (S168) .

According to the above processing, when calculating the number _N1 of vending machines that can be operated in a day, the travel time of the vending machines from the base to each area is also considered, so the distances from each base can be divided into each area approximately equally. In addition, since the number of routes is also calculated in consideration of the distance between the vending machines in each area, it is possible to equally divide the business area by the travel distance in each area.

FIG. 17 is a diagram showing a part of the data structure of the area division information storage unit T6. The area division information storage unit T6 includes: the area column, the belonging vending machine code column, the candidate vending machine code column, the column indicating that the vending machine is about to be seized from other areas, and the statistics must be recalculated if a new candidate is selected. The recalculation column for the area of the amount. As shown in Figure 9, the area division information storage unit T6 also includes the stronghold in each area-the average moving time _M1 column between the self-vending machines, the average moving time _M2 column between the self-vending machines, and the self-vending machines that must be processed. ₂ columns for the number of sold machines N, and a column for statistics (total number of routes). Fig. 17(a) assumes a case where a plurality of points are classified into regions as shown in Fig. 15(a), and explains it. At this time, because the point a is classified in area 1, "a" is stored in the corresponding "Vending Machine Code" column in the area column "1". In addition, since the point c is taken as a candidate in area 2, "c" is stored in the corresponding "candidate self-vending machine code" column in the area column "2". Although point w belongs to area 4, because it is a candidate in area 3, "w" is also stored in the corresponding "attributed self-vending machine code" column in the area column "4", and "w" is stored in the area column "3". "w" is also stored in the column of "alternate vending machine code" corresponding to ". Here, for example, in the area 3, when the point w is selected as a candidate, it is necessary to recalculate the statistics of the area 3. At this time, a flag will be stored in the recalculation column corresponding to area 3. Thereby, the statistic calculation unit 136 can grasp the regions where the recalculation of the statistic is required, and recalculate the statistic only for the marked region. The result calculated by the statistics calculation unit 136 is stored in the base of the area-the average moving time between vending machines _M1 column, the average moving time between vending machines _M2 column, the number of self-vending machines that need to be processed _N2 columns and Statistics (total number of routes) column.

In addition, point w has already been acquired by area 3. When it is captured by area 4 immediately before processing, as shown in Figure 17(b), the corresponding point "w" in the area column "4" will be Enter markup. Therefore, the point w cannot be selected as the next candidate for the region 3 and other regions.

According to the area simulation device 100 in this embodiment, since the vending machines are acquired sequentially from the area where the total number of routes and other statistical quantities are the smallest, the statistical quantities in all areas can be equally distributed. In addition, since the distance between the vending machines is shortened when the candidate vending machines are selected in each area, the travel time in each area can be reduced, and the travel time in the entire area can also be reduced. Thereby, work efficiency in a sales area can be improved.

18 to 23 show screens for parameter setting and initial setting. Fig. 18 shows a screen for selecting a division method. Here, "Tokyo 2" is selected as the division target site. In addition, the selection types of the division method include "seed point manual setting" and "seed point automatic setting". Here, select "Seed point manual setting".

FIG. 19 shows a setting screen of the basic condition for division. In the business area, set the working time (operating time) of each operator, the operating time on each vending machine, the movement speed between the base and the vending machine, and the distance between the vending machine and the vending machine. Movement speed, distance magnification, and the limited distance for obtaining vending machines. Here, set the working time of each operator as "7 hours and 30 minutes", the operating time on each vending machine as "20 minutes", and the moving speed between the base and the vending machine as "50km/h" , The moving speed between the vending machine and the vending machine is "50km/h", the distance multiplier is "1", and the limited distance to obtain the vending machine is "10km". These parameters are used to calculate the number of routes in each area explained with reference to FIG. 16 .

At this time, if the distance magnification is set to "2", in the processing of step 160 and step 162 in Fig. 16, the total distance from the base to each vending machine and the distance from each vending machine to the nearest n vending machines The total distance of is calculated by twice the value to obtain the average moving time M ₁ and the average moving time M ₂ . The number of routes in each area is calculated from the travel time calculated from the movement distance between bases and vending machines, and between vending machines and vending machines, and the operating time of each vending machine. However, by setting the distance appropriately The multiplier multiplies the movement time by a weighted value. In this embodiment, the number of routes is calculated using the straight-line distance between the base and the vending machine and between the vending machine and the vending machine. However, when actually moving between bases and vending machines and between vending machines and vending machines, most of them pass through winding roads or roads with complicated road conditions. Therefore, by setting a predetermined distance magnification as the regional characteristics of each business area, the actual travel distance can be reflected in the number of lines.

In addition, if the limit distance for obtaining self-vending machines is set to be "10km", then in step 146 of Fig. 14, any self-vending machines that have been obtained by the area beyond the distance of "10km" cannot acquired by the region. Therefore, the shortest distance between the vending machines in each area can be limited to 10 km or less, and the business area can be divided into a plurality of area blocks. The limited distance for obtaining vending machines can be appropriately set according to the size of the business area to be divided.

When "seed point manual setting" is selected on the division method selection screen shown in Fig. 18, a seed point setting screen is displayed as shown in Fig. 20 . As shown in FIG. 20( a ), the user can set the seed point from the vending machine list, and also, as shown in FIG. 20( b ), can also set the seed point from the map.

As shown in FIG. 20(b), once the seed point is set, the set seed point will be displayed on the map. Here, points representing vending machines are displayed on the map with "●". In addition, "○" is circled around "●" for the vending machine set as the initial seed point. The setting display includes the display screen of "Vending Machine Information" and the display screen of "Statistics Information". Vending machine information.

In addition, when "seed point automatic setting" is selected on the division method selection screen shown in FIG. 18 , the area number input screen is displayed as shown in FIG. 21 . Here, the user inputs the number of areas (the number of seed points) belonging to the site to be divided. Here, set the number of regions to "6".

Next, a weighting value setting screen is displayed as shown in FIG. 22 . For example, when the areas are 1 to 6, the number of routes in any one area can be multiplied by the weighted value. The weighting values set here are used to calculate statistics in each area. For example, here, a weighting value of 2 is set for the region 4 . Therefore, when calculating the total number of links shown in FIG. 16 , the statistic calculation unit 136 compares the number of links in other areas with a value twice the number of links calculated in the area "4". In this way, the number of routes in the area 4 is finally set to approximately half of the other areas. For example, when a timer operator is assigned as the person in charge of the area 4, such weighting value setting can be performed.

Next, a combination specifying screen is displayed as shown in FIG. 23 . Here, among a plurality of vending machines, it is possible to designate a combination of vending machines to be divided into the same area. For example, the user can specify to divide the vending machines located in the same building, the vending machines arranged side by side in the same base, or the vending machines at the same parking place of the delivery vehicle, etc. to be divided into the same area to improve the overall efficiency. Efficient vending machine combination. For example, point c and point d are designated and combined here. At this time, when the candidate selection processing unit 116 selects one of point c or point d as a candidate in one area, the other of point c or point d is also selected. Choose to be an alternate in this area. The statistic calculation unit 136 calculates the statistic in consideration of all the points for which the combination is specified. The point c and the point d thus specified in combination are acquired by one area at the same time.

In addition, as shown in FIG. 37 , in addition to the data structure shown in FIG. 4 , the vending machine information storage unit T3 can also store preset information on a combination of vending machines. Here, for example, vending machines with codes "b", "c" and "d" are set up in the same building, and their names are "round building 1", "round building 2" and "round building 3". ", because they are set in the same building, so their plane positions are approximately equal, which are the coordinates "x2, y2". In addition, the heights of the vending machines whose codes are "b", "c" and "d" are "2 floors", "5 floors" and "8 floors" respectively. When a vending machine point of such a specified combination is selected as a candidate, the statistic calculation unit 136 calculates a statistic in consideration of the total time of operation time of each vending machine and the travel time in the height direction between the points of the specified combination.

In addition, for example, the vending machines with the vending machine codes "e" and "f" are installed side by side in training center A, and the names are "training center A1" and "training center A2". Their plane positions are roughly equal, and they are all coordinates "(x3, y3)". In addition, the heights of the vending machines with codes "e" and "f" are both "ground". When selecting the points of the vending machines whose combination is specified in this way as a candidate, the statistic calculation unit 136 may calculate the statistic in consideration of the total time of operation time of the respective vending machines, regardless of the travel time between the vending machines. .

When the area division processing is performed as described above, the result is stored in the area division information storage unit T6. The user can appropriately read out the area division state from the area division information storage unit T6 and display it on the screen by the display processing unit 108 . The adjustment receiving unit 140 can receive a limited number of correction instructions from the user. The modification instructions from the user should be restricted in various states, but the adjustment receiving unit 140 can accept the modification only when the statistical difference of each area resulting from the modification is within a predetermined range, for example.

FIG. 24 is a flowchart showing the procedure of processing performed when the adjustment receiving unit 140 receives replacement processing from the user. When an instruction to replace the vending machine is received from the user (S270), the adjustment receiving unit 140 determines whether or not there is an authorization for the replacement process (S272). Here, the determination of whether or not the user has the authority to perform the replacement process can be performed by user authentication of whether or not the user has the authority. In addition, for this area division process, when multiple replacement processes have been performed, if several replacement processes are allowed, it is not necessary to perform automatic area division. Therefore, the number of times can be limited to determine whether it is within the set number of times. . In step 272, when it is judged that there is authorization for the replacement process (YES in S272), the statistic calculation unit 136 calculates the statistic in each area in the state of replacement according to the user's instruction (S274). Next, the adjustment receiving unit 140 judges whether or not the difference in the statistical amount in each area at the time of replacement is within an allowable range ( S276 ). When the statistical difference is within the allowable range (Yes in S276), the area division result reflecting the user's replacement instruction is stored in the area division information storage unit T6 as a new area division result (S278). On the other hand, when it is determined in step 272 that there is no authority (No in S272), or it is determined in step 276 that it is not within the allowable range (No in S276), the adjustment receiving unit 140 cannot receive the replacement instruction from the user (No in S276). S280), and issue a replacement notification.

As described above, according to the area division processing in this embodiment, since the vending machines are sequentially acquired in each area so that the distance between the vending machines is shortened, finally, the vending machines with the shortest distance between the areas are classified into within each region. Therefore, it is possible to divide one business area into square-by-block areas, and it is possible to reduce the moving distance between the vending machines in each area, and the like. In this way, according to the area division processing in this embodiment, the business areas can be divided efficiently to improve the touring work of the vending machines in each area. In addition, the vending machines are obtained in each area, and the statistics distribution of the plurality of vending machines included in each area is equalized, so that the operator can feel fair. Furthermore, since the above results are also displayed on the screen together with the map information, the person in charge can objectively recognize the degree of fairness.

(second embodiment)

In this embodiment, the seed point setting process in step 4 shown in FIG. 1 is different from that in the first embodiment. Here, first, a larger number of seed points than the actually necessary seed points is selected, and among the seed points, a seed point satisfying a predetermined condition is selected as the final seed point.

FIG. 25 is a flowchart showing the procedure of seed point setting processing in this embodiment. The area number setting reception unit 128 receives the setting of candidate seed points and selection conditions (S200). Here, the selection condition refers to how many seed points are finally selected from among the candidate seed points, and the like.

The seed point selection unit 130 sets candidate seed points ( S202 ) having the number set as the number of candidate seed points in the same procedure as shown in FIG. 10 . Next, the seed point selection unit 130 performs grouping ( S204 ), assigning the vending machines in the business area to one of the candidate seed points set in step 202 .

As a group, the vending machines in the business area can be assigned to the candidate seed points that are respectively located in the closest positions among the candidate seed points set in step 200 . In addition, as another example of grouping, the division processing unit 115 can perform preliminary region division in the same procedure as shown in FIGS. 13 and 14 starting from the candidate seed point set in step 200 .

Thereafter, the seed point selection unit 130 considers the grouping result and the information of the vending machines classified by each candidate seed point, and selects several candidate seed points as seed points according to the selection condition (S206).

Through the above-described processing, seed points for actually performing region division are set, and region division is performed in the same procedure as shown in FIGS. 13 and 14 (S208).

Fig. 26 is a diagram showing a setting screen of candidate seed points and selection conditions in this embodiment. Here, "6" is input as a seed point candidate. In addition, the following conditions are displayed as selection conditions: "According to the division result, how many are selected from the group with a large number of vending machines as candidate seed points?" and "According to the division result, how many are selected from the group with a small number of vending machines?" as a candidate seed point?". Here, "3" is input for the condition "How many are selected from the group with a small number of vending machines as candidate seed points based on the division result?".

When inputting in this way, first select 6 vending machines as candidate seed points, and assign other vending machines to one of the 6 vending machines for grouping. Then, detect the number of vending machines in each group, select 3 groups in order from the group with few vending machines among the 6 groups, and select the candidate seed points in these 3 groups as the final seed point.

According to the area division process of this embodiment, each seed point is used as a starting point to perform area division, so that the number of routes in multiple areas is equalized. Therefore, when a seed point is set in an area densely populated with vending machines, the movement distance from the seed point to the adjacent vending machines becomes smaller. Therefore, compared with other areas, the area including the seed point may include many vending machines even if the number of routes is the same. When the number of self-sales in a plurality of areas is greatly different, even if the number of routes is set to be the same, there may be a sense of unfairness among operators.

In addition, when only one vending machine is set as a seed point far away from other vending machines, the moving distance from the seed point to the adjacent vending machines will be increased. Therefore, in the region including the seed point, even if the region is divided according to the same route data as other regions in the calculation process of the number of routes in the region division process, an inefficient region division result may actually be produced.

According to the area division process of this embodiment, it is possible to avoid setting seed points in areas where vending machines are densely populated, or to set seed points at positions far away from other vending machines. At the same time, it is also possible to divide the area in such a way that the number of vending machines included in each area is close to each other. Thereby, it is possible to reduce the feeling of unfairness of the operators in charge of each area.

(Example 3)

In this embodiment, the setting of the seed points can also be performed automatically, which is different from the first embodiment and the second embodiment.

FIG. 27 is a block diagram showing the structure of the area simulation device 100 of this embodiment. In this embodiment, the area simulation device 100 is different from the area simulation device 100 in the first embodiment in that it has a division state determination unit 120 . In FIG. 27 , the same reference numerals are assigned to the same components as those shown in FIG. 3 , and explanations thereof are appropriately omitted.

After the division process is performed by the division processing unit 115, the division state judging section 120 compares the statistics in each divided region to judge whether the division is appropriate; and the initial setting, the division processing is performed again.

FIG. 28 is a block diagram showing in detail the initialization unit 114 of this embodiment. The initial setting unit 114 has a route number setting reception unit 142 and an area number calculation unit 144 in addition to the configuration described with reference to FIG. 5 in the first embodiment. The seed point setting method receiving unit 124 receives a selection of seed point manual setting, seed point automatic setting, and route number setting as a seed point setting method. When the seed point setting method receiving unit 124 receives the manual setting of the seed point or the automatic setting of the seed point, it performs the same process as that of the first embodiment or the second embodiment. When the seed point setting method receiving unit 124 receives the selection of the number of routes setting, the number of routes setting receiving unit 142 receives the setting of the number of lines from the user, and the area number calculating unit 144 sets the number of routes according to the number of routes received by the receiving unit 142. The number of routes calculates the number of regions.

FIG. 29 is a block diagram showing in detail the logic storage unit T7 in this embodiment. In addition to the configuration shown in FIG. 8 in the first embodiment, the logical storage unit T7 has a logical storage unit T7d for area number calculation. The logic storage section T7d stores logic necessary for the area number calculation section 144 to calculate the number of areas.

FIG. 30 is a flowchart showing the logic used by the number of areas calculation unit 144 to calculate the number of areas into which business areas are divided, stored in the number of areas calculation logic storage unit T7d.

The route number setting receiving unit 142 receives an input of the number of routes in each area from the user ( S220 ). The number of routes here refers to the amount of work each operator can do in one day, and therefore, "1" is set as the initial value of the number of routes in each area. However, for example, the number of routes may be set to 1 or more during busy periods, and the number of routes may be set to 1 or less in consideration of business hours other than tour operations. Next, the number-of-areas calculation unit 144 calculates the number of areas required in the business area (S222).

FIG. 31 is a flowchart showing the logic stored in the area number calculation logic storage unit T7d for the area number calculation unit 144 to calculate the number of areas necessary for the business area. This processing is performed in the same procedure as the calculation of the total number of routes in each area described with reference to FIG. 16 . The number of areas calculation unit 144 appropriately refers to the site information data stored in the site information storage unit T2, the vending machine information data stored in the vending machine information storage unit T3, and the parameters stored in the parameter storage unit T4, as follows: to calculate the total number of routes.

First, the area count calculation unit 144 calculates the average travel time M ₃ from the base to the vending machines in the business area (S250). The total distance from the base to each vending machine is obtained first, and then the total travel time is obtained by dividing the total distance by the moving speed between the base and the vending machine set by the parameter setting unit 110 . Next, divide the total travel time by the number of all vending machines to obtain M ₃ .

Next, the area count calculation unit 144 calculates the average travel time M ₄ between the vending machines (S252). First, the total distance from each vending machine to the nearest n vending machines is obtained, and then the total distance is divided by the moving speed between the vending machines set by the parameter setting unit 110 to obtain the total travel time . Next, by dividing this total travel time by n, average travel times m ₁ to m _n from each vending machine to another vending machine are obtained. Then, the total time of these average travel times m ₁ to m _n is obtained and divided by the number of all vending machines to calculate M ₄ .

Next, the number of areas calculation unit 144 calculates the number N ₃ of vending machines that can be operated in a day in the business area (S254). Since the total operating time of a day is T _Z =M ₃ ×2+M ₄ (N ₃ -1)+T×N ₃ (T is the average operating time of each vending machine), this formula is transformed to calculate N ₃ =(T _Z −M ₃ ×2+M ₄ )/(M ₄ +T).

On the other hand, the number of areas calculation unit 144 calculates the number N ₄ of vending machines that must be handled per day on average (S256). First, by calculating the monthly filling times of each vending machine, and adding up the filling times, the monthly filling times W are calculated. Next, N ₄ =W/20 is obtained by setting the number of working days of each operator in one month as 4 weeks×5 days=20.

Thereafter, the number of areas calculation unit 144 divides the average number _N4 of self-vending machines that must be processed per day by the number _N3 of self-service vending machines that can be operated in one day, thereby calculating the number of routes necessary per day= _N4 / _N3 ( S258). The number of areas calculation unit 144 divides the number of required routes calculated in this way by the number of routes input in step 220 of FIG. 30 to calculate the number of areas required in the business area (S260).

Referring back to FIG. 30 , the seed point selection unit 130 sets seed points twice the calculated required number of regions in the same procedure as shown in FIG. 10 ( S224 ).

Next, the seed point selection section 130 performs grouping in the same procedure as described in the second embodiment (S226). Thereafter, the seed point selection unit 130 considers the grouping result and the number of vending machines belonging to various subpoints, and sequentially selects the seed points with the necessary number of regions from the seed points with fewer vending machines. Here, the selected seed points Set as the final seed point (S228).

Through the above processing, seed points for actually performing region division are set, and region division is performed in the same procedure as shown in FIGS. 13 and 14 (S230).

Next, the division state determination unit 120 calculates the number of lines in the area actually divided by the condition, and evaluates the division state (S232). As a result, if the calculated route number is within the allowable range (YES at S234), the process ends, and the result is displayed. If it is not within the allowable range (No in S234), the process returns to step 222, and a new number of areas is calculated.

32 to 34 show screens for parameter setting and initial setting in this embodiment. Fig. 32 shows a screen for selecting a division method. In this embodiment, in addition to the content described with reference to FIG. 18 for the first embodiment, the selection category as a division method includes "number of routes setting". Here, "Number of routes setting" is selected as the division method.

FIG. 33 shows a setting screen for basic conditions for division. In this embodiment, in addition to the contents explained with reference to FIG. 19 in the first embodiment, the number of working days per week is included as one item. Here, set the number of working days per week to "5".

On the screen for selecting the division method shown in FIG. 32 , as shown in FIG. 34 , when "Number of routes setting" is selected, an input screen for the number of routes is displayed. Here, the user inputs the number of routes in each area; in this embodiment, "1" is input as the number of routes. Next, the user inputs the allowable error range, and here, +10% and -10% are set. Therefore, area division is performed so that the number of routes in each area is 0.9 to 1.1.

According to the area division processing of this embodiment, the business area to be divided can be divided into a plurality of areas only by setting the number of routes in each area. Business areas are automatically divided so that the statistics of a plurality of vending machines included in each area are evenly distributed by using the area simulation device 100 , so that objective area division can be performed and operators can feel fair. In addition, since the vending machines are sequentially acquired in each area so that the distance between the vending machines is shortened, the vending machines with the shortest distance between the areas are finally classified into each area. Therefore, it is possible to divide a business area into areas in units of blocks, and at the same time, it is possible to reduce the moving distance between vending machines in each area, thereby improving the efficiency of tour management of vending machines.

(fourth embodiment)

In this embodiment, when calculating the number of routes in each area, the statistic calculation unit 136 considers the actual operating time of each vending machine stored in the vending machine information storage unit T3 to calculate the number of routes. One point is different from the first to third embodiments. In the first to third embodiments, for example, in the first embodiment, as explained in step 164 of FIG. The average operating time on the vending machine is described. However, for example, among existing vending machines, there are also types that perform inventory confirmation from a remote location and types that do not use cash. Actually, the operating time of the vending machines differs depending on characteristics such as types of vending machines. In this embodiment, the statistical calculation unit 136 calculates the statistics by referring to the types and characteristics of the vending machines stored in the vending machine information storage unit T3 and reflecting the operating time set for each vending machine. The number of routes commensurate with the actual amount of operation can be calculated more accurately. In this way, the characteristics of each vending machine are stored in the vending machine information storage unit T3, and by using this information, the areas can be more strictly divided, and the workload of the operators in each area can be evenly distributed.

The processing of the statistic calculation unit 136 in this embodiment will be described with reference to FIG. 16 . Similar to the first embodiment, the statistic calculation unit 136 calculates the average moving time M ₁ from the base to the vending machines and candidate vending machines already belonging to the area (S160), and then the statistic calculation unit 136 and the first Embodiment Similarly, the average moving time M ₂ between vending machines is calculated (S162).

Next, the statistic calculation unit 136 calculates the number N ₁ of vending machines that can be operated in one day (S164). First, the statistic calculation unit 136 refers to the vending machine information storage unit T3, and calculates the total time T _o of the operation time of the already acquired vending machines and the candidate vending machines in the area. At this time, the total operating time T _Z =2×M ₁ +M ₂ ×(N ₁ −1)+T _o for one day. This formula is transformed to obtain N ₁ ={(T _Z -2M ₁ -To)/M ₂ }+1.

On the other hand, the statistic calculation unit 136 calculates the number N ₂ of vending machines that must be processed every day, as in the first embodiment (S166). Thereafter, the statistic calculation unit 136 divides the number N ₂ of self-vending machines that must be processed each day by the number N ₁ of self-vending machines that can be operated in one day, and thus calculates the number of routes in each area=N ₂ /N ₁ (S168 ).

Fig. 36 is a diagram showing another example of a part of the data structure of the vending machine information storage unit T3. Here, the vending machine information data includes "vending machine classification", "parking status", and the like for each vending machine. Here, the type of vending machine can be identified based on the amount of operation of the vending machine. For example, a vending machine that does not need to collect sales money and can predict the replenishment amount because it does not use cash and has a communication function can be classified as "A", and a self-vending machine that does not need to collect sales money but cannot predict the replenishment amount can be classified as "A". B", classify as "C" the self-vending machines that need to recover the sales money, replenish the change money, and confirm the replenishment amount. In addition, the parking situation can be determined according to the ease of parking the delivery vehicle. For example, "1" is set to be able to park next to the vending machine, and "2" is set to "2" if the distance between the vending machine and the parking position is within, for example, 20 m. When the distance between the car positions exceeds 20 m, "3" is set. The statistic calculation unit 136 can calculate the operating time of each vending machine according to the classification of the respective vending machines, the parking situation, the loading amount not shown in the figure, and the like. At this time, the statistic calculation unit 136 can calculate the number of routes in each of the above-mentioned areas using the operation time calculated in this way.

If it is carried out as above, the statistics calculation part 136 can refer to the vending machine information storage part T3, reflect the difference between the actual operation time of each vending machine and the situation of each vending machine, and calculate the statistics. The number of routes is calculated more precisely and the workload of operators in each area can be evenly distributed. In addition, when calculating the number _N1 of vending machines that can be operated in one day, since the travel time of the vending machines from the base to each area is also taken into consideration, the distances between each area and the base can be divided into each area approximately equally. . In addition, since the number of routes is calculated in consideration of the distance between the vending machines in each area, it is possible to divide the business area evenly with the travel distance in each area.

(Example 5)

FIG. 35 is a diagram showing an area simulation system 146 including the area simulation device 100 described in the first to fourth embodiments. The processing from the user described in the first to fourth embodiments can be performed from the user terminal 150 via the network 148 . In this embodiment, the user terminal 150 only needs to be a terminal device capable of communicating with the area simulation device 100 via the network 148 . For example, the user terminal 150 may be a PC, a PDA, a mobile phone, or other arbitrary hardware.

In this way, the user can carry the user terminal 150 and send instructions necessary for the area dividing process to the area simulation device 100 while actually going around the business area where the vending machines are installed. In this way, it is possible to reflect the actual on-site situation, for example, to input a combination designation to the combination designation receiving unit 132 or to input a replacement process to the adjustment receiving unit 140 .

In addition, the area simulation device 100 described in the first to fourth embodiments may have a data registration receiver for receiving various data registrations such as site information data and vending machine information data, in addition to the configuration described in each embodiment.

FIG. 38 is a block diagram showing a configuration in which the area simulation device 100 in the first embodiment has a data registration receiving unit 152 . The data registration receiving unit 152 receives various data registrations from users, and stores these data in the base information storage unit T2 or the vending machine information storage unit T3. Thereby, the user can carry out various data registrations while holding the user terminal 150 and actually going around the business area where the vending machines are installed. Therefore, more accurate and accurate information can be stored in the base information storage unit T2 and the vending machine information storage unit T3. In addition, although various data are registered in the base information storage unit T2 or the vending machine information storage unit T3 in advance, when the situation on the spot changes, the data can be quickly updated. By accurately and quickly arranging various data stored in the base information storage unit T2 and the vending machine information storage unit T3, it is possible to appropriately divide the target business area.

39 and 40 show screens for registering vending machine information data. Fig. 39(a) shows a screen for inputting the vending machine code of the vending machine for registration data. Fig. 39(b) shows an input screen of vending machine information data corresponding to the vending machine code input in Fig. 39(a). Here, in FIG. 39( a ), "b" is input as the vending machine code. When there is a designation of the vending machine code from the user, the data registration receiving unit 152 refers to the vending machine information storage unit T3 to determine whether the vending machine information data of the corresponding vending machine has been stored. When the vending machine information data of the corresponding vending machine has been stored, the data registration receiving unit 152 reads out the information data of the vending machine. The vending machine information data read by the data registration receiving unit 152 is shown on the screen of FIG. 39( b ). On the other hand, when the vending machine information data of the corresponding vending machine has not been registered yet, or when there is an unregistered item, the screen of FIG. 39( b ) is displayed in a blank state. Here, the vending machine information data with the vending machine code "b" is displayed, the base code of the vending machine is "1000", the name is "round building 1", and the location coordinates are [X=X ₂ ] , [Y=Y ₂ ], the height is "2 floors". When modification is required, the user can change these vending machine information data. In addition, since the operation time is displayed as a blank column, the operation time can be input by the user.

As shown in Figure 40 (a), when the input of the screen of Figure 39 (b) ended, the data registration receiving part 152 just inquired whether the self-vending machine with the self-vending machine code as "b" and a certain self-vending machine Combination specified. Here, when the user selects "No", the registration of the vending machine information data with the vending machine code "b" ends. On the other hand, when the user selects "Yes", the data registration receiving unit 152 designates the vending machines for which the user specifies a combination. At this time, the data registration receiving unit 152 may input the self-vending machine code of the vending machine that the user specifies in combination, or, for example, as shown in FIG. The user is presented with a list of vending machines with a high possibility of specifying a combination. At this time, the user can select a vending machine designated to be combined with the vending machine with the vending machine code "b" from among the vending machines included in the table.

In the present embodiment, necessary information can be sent and received from the user terminal 150 to the area simulation device 100 via the network 148, and therefore, information necessary for area division can be sent to the area simulation device 100 while actually touring the business area. information. Therefore, for example, various data can be updated accurately and quickly, and the accuracy of area division can be optimally improved.

The present invention has been described above using examples. The embodiment is an example, so that those skilled in the art can understand that various modifications can be formed in the combination of each structural element and each processing procedure of the embodiment, and such modifications also belong to the scope of the present invention. Hereinafter, such a modified example will be described.

The region division processing described with reference to FIGS. 13 to 15 in the first embodiment can be performed in various orders. For example, in the candidate selection process of step 104 in FIG. 13 , the vending machine that is closest to the center of gravity of the vending machine that has been detected in each area is used as a candidate ( FIG. 14 , S130 and S132 ). In each area, the vending machine that is closest to the vending machine set as the seed point is detected as a candidate. In this case, it can be judged by the same processing as in FIG. 14 whether or not to decide whether to use the detected vending machine as a candidate.

In addition, it was described in the third embodiment that when the number of courses is input, the number of seed points is automatically set. However, when the initial setting unit 114 receives an input of the number of routes from the user, it can also refer to the logic storage unit T7, calculate the number of areas through the processing shown in FIG. 31 , and present the necessary number of areas to the user. At this time, the user can choose to set the seed point manually or automatically, and can make fine adjustments such as weighting value setting as needed.

In addition, in the above embodiments, the total number of routes in each area is taken as a statistical quantity, and this is an example for description. However, for example, the number of vending machines included in each area, the average loading operation time of each vending machine, the daily average loading times of each vending machine, the distance between each vending machine and the base can also be used in each area. Average distance, average distance between vending machines, number of vending machines per route, total sales, average sales per vending machine, etc. Statistics other than the number of routes are equally distributed. For example, when the average sales of each vending machine is used as a statistical quantity, the sales in each area can be equally divided into regions. It is also possible to combine such processing with the processing described in the second and third embodiments in which candidate seed points are set and grouped with more seed points than actually required. At this time, it is possible to properly set the seed point with an equal number of self-vending machines included in each area. Finally, the number of routes in each area can be evenly distributed to a certain extent, and it is also possible to make the sales in each area equal amount. In this way, the operator's sense of fairness can be further improved.

In addition, the above-mentioned embodiment has described the example of dividing the business area into a plurality of areas, and the same method can also be used when setting a plurality of business areas. At this time, the bases in each business area can also be set by the same method as the method of setting the seed point in the above-mentioned embodiment.

Possibility of industrial use

As mentioned above, according to the present invention, the area where a plurality of vending machines are installed can be objectively divided into a plurality of responsible areas, so that the operators engaged in the tour management of the vending machines feel fair. In addition, according to the present invention, the area where a plurality of vending machines are installed can be divided into a plurality of responsible areas, so that the workload of the operators engaged in the tour management of the vending machines can be evenly distributed. According to the present invention, an area in which a plurality of vending machines is installed can be objectively divided into areas in charge of operators engaged in tour management of vending machines while visually grasping the divided state. According to the present invention, an area where a plurality of vending machines are installed can be divided into a plurality of responsible areas, so as to improve the tour work efficiency of the operator who is engaged in the tour management of the vending machines. According to the present invention, the area where a plurality of vending machines are installed can be divided into a plurality of responsible areas, so as to reduce the total workload of all operators engaged in the tour management of the vending machines.

Claims (19)

1. An area division system that divides an area where a plurality of vending machines are installed into areas in charge of operators engaged in vending machine tour management, characterized in that it has: The number of people, setting a plurality of areas including at least one vending machine in the above area; the calculation part, which calculates the statistics determined according to the characteristics of the vending machines included in each area; the processing part, which considers the above statistics After selecting a specific area based on the specified amount, the process of adding vending machines in the specific area to expand the area is repeated, and when the specified conditions are met, the process is terminated, and the acquired area is defined as the above-mentioned plurality of persons in charge. area of responsibility. 2. The area division system according to claim 1, further comprising a candidate selection unit for selecting a candidate automatic vending machine to be added for each area, and the calculation unit calculates the number of additional automatic vending machines for each area. The above-mentioned statistics in the case of a vending machine, the processing unit selects the above-mentioned specific area in consideration of the above-mentioned statistics in the case of adding the candidate automatic vending machine. 3. The area division system according to claim 2, wherein the processing unit selects the specific area in the state where the vending machine is added in any area, and reduces the difference of the statistics in each area. 4. The area division system according to claim 2 or 3, further comprising a position information storage unit storing position information of the automatic vending machine, and the candidate selection unit selects the candidate by referring to the position information of the automatic vending machine. . 5. The area division system according to claim 4, wherein the candidate selection unit sequentially selects based on the position information of the vending machines assigned to each person in charge and considering the distance from the representative point to be determined. 6. The area division system according to claim 5, wherein the candidate selection unit specifies the representative location based on the location information of all the vending machines assigned to each person in charge. 7. The area division system according to claim 5 or 6, wherein the candidate selection unit determines the center of gravity of the positions of the automatic vending machines assigned to each person in charge as the representative point. 8. The area division system according to any one of claims 1 to 7, wherein the statistical quantity is the workload when each responsible person tours and operates the vending machines included in each responsible area . 9. The area classification system according to claim 8, wherein the calculation unit calculates the statistics in consideration of travel time between the vending machines. 10. The area division system according to any one of claims 1 to 9, wherein the information related to the characteristics of each of the above-mentioned automatic vending machines includes the location information of each of the above-mentioned automatic vending machines, and the area division system also includes It has a characteristic information storage part which stores the positional information of this automatic vending machine, and the said calculation part calculates the travel time between the said automatic vending machines based on the positional information between the said automatic vending machines. 11. The area division system according to any one of claims 8 to 10, wherein said area includes bases; Statistics. 12. The zoning system according to any one of claims 8 to 11, wherein the calculation unit calculates the statistics in consideration of the operating time of each of the automatic vending machines. 13. The area classification system according to any one of claims 8 to 12, wherein the calculating unit calculates the statistics according to the type of each of the automatic vending machines. 14. The area division system according to any one of claims 1 to 13, wherein the processing unit adds the above-mentioned automatic vending machines in each area, so that the automatic vending machines included in each responsible area The distance is within the prescribed limit distance. 15. The area division system according to any one of claims 1 to 14, further comprising a weighted value setting unit that adds a weighted value to the statistical quantity for each area, and the calculation unit considers the weighted value values to calculate the above statistics. 16. The area division system according to any one of claims 1 to 15, further comprising a combination designation receiving unit that receives, among the plurality of automatic vending machines, the automatic vending machines that should be included in the same area in charge. In the designation of a combination of vending machines, the initial setting unit and the processing unit include the automatic vending machines in the designated combination in the same area. 17. The area division system according to any one of claims 1 to 16, further comprising: a map information storage unit for storing map information of the above-mentioned areas; The vending machines are displayed together with the above map information to show the difference of each responsible area like this. 18. The zoning system according to any one of claims 1 to 17, further comprising a characteristic information receiving unit that receives input of information on the characteristics of the automatic vending machine through a network. 19. A data structure for use when dividing an area where a plurality of vending machines are installed into areas in charge of operators who perform tour management of vending machines, comprising: A responsible area distinguishes and stores the identification information of the vending machines that have already belonged to each responsible area and the identification information of the candidate automatic vending machines that will belong to each responsible area; It is a statistic calculated from information on the characteristics of the vending machines in the area in charge and the characteristics of the vending machines that are candidates for each area in charge.

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