CN106059816A - Transfer warehouse site selection method and system - Google Patents
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Abstract
The invention discloses a transfer warehouse site selection method and system. The method comprises the steps of: acquiring preset business volume of finished automobiles of each city; according to the preset business volume of the finished automobiles of each city, acquiring a list of city coordinates meeting a preset acquisition condition; using the business volume of the finished automobiles corresponding to each city coordinate in the list of city coordinates as a weight, and respectively performing weighting on each city coordinate in the list of city coordinates to obtain a new list of city coordinates; performing cluster analysis on each city coordinate in the new list of city coordinates, and testing cluster distribution under the condition of a preset number of clusters; according to the tested cluster distribution under the condition of the preset number of clusters, obtaining the cluster distribution meeting a preset screening condition through screening; and performing transfer warehouse site selection according to the cluster distribution meeting the preset screening condition which is obtained through screening. According to the method and system provided by the invention, influence of city volume of business is considered, a transfer warehouse is established according to the screened cluster distribution meeting requirements, materials can be delivered timely and effectively, and thus, the method and system provided by the invention are of great significance to network planning, network optimization and like.
Description
Technical field
The present invention relates to logistics management technical field, particularly relate to a kind of transfer storage facility site selecting method and system.
Background technology
Along with the high speed development of automobile industry, automobile portfolio constantly increases, and the network planning and optimization are proposed challenge.
Transfer storage facility is the terminal of logistics, and existing transfer storage facility addressing does not accounts for the impact of city portfolio, city portfolio, bag
Include influx and discharge, be to weigh logistics transportation networks to run and the important parameter of state, the addressing of the most existing transfer storage facility
Point does not often meet actual application needs, is unfavorable for logistics.
Summary of the invention
Based on above-mentioned situation, the present invention proposes a kind of transfer storage facility site selecting method and system, thing of in time, effectively providing and delivering
Material, is suitable for application.
To achieve these goals, the embodiment of technical solution of the present invention is:
A kind of transfer storage facility site selecting method, comprises the following steps:
Obtain the car load portfolio presetting each city；
The city list of coordinates meeting default acquisition condition is obtained according to the described car load portfolio presetting each city；
Using car load portfolio corresponding for each city coordinate in the list of coordinates of described city as weight, respectively to described city
Each city coordinate in city's list of coordinates is weighted weight, obtains new city list of coordinates；
Each city coordinate in described new city list of coordinates carries out cluster analysis, and test is preset under cluster number
Clustering distribution；
Filter out according to the clustering distribution under the default cluster number that obtains of test and meet the cluster of default screening conditions and divide
Cloth；
The clustering distribution meeting default screening conditions according to filtering out carries out transfer storage facility addressing.
A kind of transfer storage facility site selection system, including:
Portfolio acquisition module, for obtaining the car load portfolio in each city default；
Coordinate obtaining module, meets default acquisition condition for obtaining according to the described car load portfolio presetting each city
City list of coordinates；
Weight increase module, for using car load portfolio corresponding for each city coordinate in the list of coordinates of described city as
Weight, is weighted weight respectively, obtains new city list of coordinates each city coordinate in the list of coordinates of described city；
Cluster Analysis module, for each city coordinate in described new city list of coordinates is carried out cluster analysis,
The clustering distribution under cluster number is preset in test；
Clustering distribution screening module, the clustering distribution under the default cluster number obtained according to test filters out and meets
Preset the clustering distribution of screening conditions；
Transfer storage facility addressing module, for carrying out transfer storage facility choosing according to the clustering distribution meeting default screening conditions filtered out
Location.
Compared with prior art, the invention have the benefit that transfer storage facility site selecting method of the present invention and system, obtain respectively
Preset the car load portfolio in each city, and obtain the city list of coordinates meeting default acquisition condition；Will be with this city coordinate
Each city in this city list of coordinates, as weight, is sat by car load portfolio that in list, each city coordinate is corresponding respectively
Mark is weighted weight；Each city coordinate in city list of coordinates new after weighted is carried out cluster analysis；According to cluster
The clustering distribution of default screening conditions that what analysis result filtered out meet carries out transfer storage facility addressing, and the present invention considers city portfolio
Impact, can filter out simultaneously and meet the clustering distribution of default screening conditions and set up transfer storage facility, thing of in time, effectively providing and delivering
Material, map network planning, the network optimization etc. are significant.
Accompanying drawing explanation
Fig. 1 is transfer storage facility site selecting method flow chart in an embodiment；
Fig. 2 is for based on transfer storage facility site selecting method flow chart in the concrete example of method one shown in Fig. 1；
Fig. 3 is transfer storage facility site selection system structural representation in an embodiment.
Detailed description of the invention
For making the purpose of the present invention, technical scheme and advantage clearer, below in conjunction with drawings and Examples, to this
Invention is described in further detail.Should be appreciated that detailed description of the invention described herein only in order to explain the present invention,
Do not limit protection scope of the present invention.
Transfer storage facility site selecting method in one embodiment, as it is shown in figure 1, comprise the following steps:
Step S101: obtain the car load portfolio presetting each city；
Step S102: obtain the city seat meeting default acquisition condition according to the described car load portfolio presetting each city
Mark list；
Step S103: using car load portfolio corresponding for each city coordinate in the list of coordinates of described city as weight, point
Other be weighted each city coordinate in the list of coordinates of described city heavily, obtains new city list of coordinates；
Step S104: each city coordinate in described new city list of coordinates carries out cluster analysis, test is preset
Clustering distribution under cluster number；
Step S105: filter out according to the clustering distribution under the default cluster number that test obtains and meet default screening conditions
Clustering distribution；
Step S106: the clustering distribution meeting default screening conditions according to filtering out carries out transfer storage facility addressing.
It is evidenced from the above discussion that, transfer storage facility site selecting method of the present invention, it is considered to the impact of city portfolio, can screen simultaneously
The clustering distribution going out to meet default screening conditions sets up transfer storage facility, in time, material dispensing effectively, and map network planning, network
Optimization etc. are significant.
Additionally, in a concrete example, obtain to meet to preset according to the described car load portfolio presetting each city and obtain
The step of the city list of coordinates taking condition includes:
Respectively the described car load portfolio presetting each city is compared with pre-set business amount threshold value；
Obtain the car load portfolio city coordinate more than described pre-set business amount threshold value, obtain meeting described default acquisition bar
The city list of coordinates of part.
City portfolio, including influx and discharge, is to weigh logistics transportation networks to run and the important parameter of state,
City less to portfolio is rejected, and obtains the city coordinate that portfolio is many, is suitable for application.
Additionally, in a concrete example, each according in described new city list of coordinates of described default cluster number
The number of individual city coordinate is arranged.
The number of the newest each city coordinate in the list of coordinates of city is 10, and arranging and presetting cluster number is 4-
7, do not take the numerical value that two is less or bigger, the clustering distribution under test difference cluster number, result more corresponds to actual needs.
Additionally, in a concrete example, described clustering distribution includes several cluster centre coordinates and described new
The cluster ownership of each city coordinate in the list of coordinates of city.
After cluster analysis, we can obtain the cluster centre coordinates under different cluster number and each coordinate
Cluster ownership, for example with K-means clustering methodology, the clustering distribution under the conditions of test difference cluster number, K-means gathers
First alanysis method arbitrarily selects k object (city) as initial cluster center from n data object (city)；And for
Remaining other object (city), then according to them and the similarity (distance) of these cluster centres, assign these to respectively
(cluster centre representated by) cluster most like with it；Calculate each cluster centre (this cluster being obtained new cluster the most again
In the average of all objects)；Constantly repeat this process until canonical measure function starts convergence.
Additionally, in a concrete example, filter out symbol according to the clustering distribution under the default cluster number that test obtains
The step closing the clustering distribution presetting screening conditions includes:
Each cluster centre is obtained to the distance presetting main engine plants in each clustering distribution；
Each clustering distribution calculates according to the cluster ownership of each city coordinate in described new city list of coordinates
Each cluster centre is to the distance in corresponding city；
According to the distance of cluster centre each in each clustering distribution to corresponding city, obtain each cluster centre to its
Cost of transportation to Yingcheng City；
According to the distance of cluster centre each in each clustering distribution to default main engine plants, each cluster centre is to corresponding city
The distance in city, and each cluster centre filters out to the cost of transportation in corresponding city and meets the poly-of described default screening conditions
Class is distributed.
Main engine plants are main port of shipments, obtain each cluster centre distance to default main engine plants in each clustering distribution,
According to the distance of each cluster centre to default main engine plants, obtain each cluster centre longest distance to default main engine plants, average departure
From, and beyond presetting main engine plants' number of main engine plants' distance；
According to the distance of each cluster centre to corresponding city, obtain the shortest to corresponding city of each cluster centre
Distance, longest distance, average distance and the city number beyond default city distance；According to each cluster centre to corresponding
The beeline in city obtains each cluster centre of each clustering distribution average beeline to corresponding city；In like manner root
The each cluster centre of each clustering distribution is obtained to corresponding according to the longest distance of each cluster centre to corresponding city
The average longest distance in city and maximum longest distance；Obtain to the average distance in corresponding city according to each cluster centre
To each cluster centre of each clustering distribution to corresponding city again average after average distance；
According to the distance of cluster centre each in each clustering distribution to corresponding city, and single kilometer of cost of transportation,
The average of haulage vehicle loads car load amount, obtains each cluster centre cost of transportation to corresponding city；
According to each cluster centre in above-mentioned each clustering distribution to the default distance of main engine plants, longest distance, average distance,
Beyond presetting main engine plants' number of main engine plants distances, the distance of each cluster centre to corresponding city, average beeline, put down
All longest distance, maximum longest distance, again average after average distance, beyond presetting the city number of city distance, with
And each cluster centre filters out the clustering distribution meeting default screening conditions to the cost of transportation in corresponding city, described preset
Screening conditions can be arranged according to actual needs, can filter out in the optimal classification number of cluster and the optimal of each cluster
The heart.
In order to be more fully understood that said method, the application of a transfer storage facility site selecting method of the present invention detailed below is real
Example.
As in figure 2 it is shown, this application example may comprise steps of:
Step S201: obtain the car load portfolio presetting each city；
Step S202: respectively the described car load portfolio presetting each city is compared with pre-set business amount threshold value；
Step S203: obtain car load portfolio more than the city coordinate of described pre-set business amount threshold value, obtains meeting default
The city list of coordinates of acquisition condition；
Step S204: utilize VBA using car load portfolio corresponding for each city coordinate in the list of coordinates of described city as
Weight, is weighted weight respectively, obtains new city list of coordinates each city coordinate in the list of coordinates of described city；
Step S205: use K-means clustering methodology to each city coordinate in described new city list of coordinates
Carrying out cluster analysis, the clustering distribution under cluster number is preset in test；Described default cluster number is sat according to described new city
The number of each city coordinate in mark list is arranged；Described clustering distribution include several cluster centre coordinates and described newly
City list of coordinates in each city coordinate cluster ownership；
First K-means clustering methodology arbitrarily selects k object (city) as just from n data object (city)
Beginning cluster centre；And for remaining other object (city), then according to they similarities (distance) with these cluster centres,
Assign these to (cluster centre representated by) cluster most like with it respectively；Calculate the most again and each obtained new cluster
Cluster centre (average of all objects in this cluster)；Constantly repeat this process until canonical measure function starts to converge to
Only.Mean square deviation is typically all used to have the following characteristics that each cluster itself is the tightest as canonical measure function .k cluster
Gather, and separate as far as possible between respectively clustering.
Step S206: obtain each cluster centre in each clustering distribution to the distance presetting main engine plants；
Main engine plants are main port of shipments, obtain each cluster centre distance to default main engine plants in each clustering distribution,
According to the distance of each cluster centre to default main engine plants, obtain each cluster centre longest distance to default main engine plants, average departure
From, and beyond presetting main engine plants' number of main engine plants' distance
Step S207: according to the cluster of each city coordinate in described new city list of coordinates in each clustering distribution
Ownership calculates each cluster centre distance to corresponding city；
According to the distance of each cluster centre to corresponding city, obtain the shortest to corresponding city of each cluster centre
Distance, longest distance, average distance and the city number beyond default city distance；According to each cluster centre to corresponding
The beeline in city obtains each cluster centre of each clustering distribution average beeline to corresponding city；In like manner root
The each cluster centre of each clustering distribution is obtained to corresponding according to the longest distance of each cluster centre to corresponding city
The average longest distance in city and maximum longest distance；Obtain to the average distance in corresponding city according to each cluster centre
To each cluster centre of each clustering distribution to corresponding city again average after average distance；
Step S208: according to the distance of cluster centre each in each clustering distribution to corresponding city, obtain each cluster
Center is to the cost of transportation in corresponding city；
According to the distance of cluster centre each in each clustering distribution to corresponding city, and single kilometer of cost of transportation,
The average of haulage vehicle loads car load amount, obtains each cluster centre cost of transportation to corresponding city；
Step S209: according to the distance of cluster centre each in each clustering distribution to default main engine plants, each cluster centre arrives
The distance in corresponding city, and each cluster centre filters out to the cost of transportation in corresponding city to meet and presets screening bar
The clustering distribution of part；
According to each cluster centre in above-mentioned each clustering distribution to the default distance of main engine plants, longest distance, average distance,
Beyond presetting main engine plants' number of main engine plants distances, the distance of each cluster centre to corresponding city, average beeline, put down
All longest distance, maximum longest distance, again average after average distance, beyond presetting the city number of city distance, with
And each cluster centre filters out the clustering distribution meeting default screening conditions to the cost of transportation in corresponding city, described preset
Screening conditions can be arranged according to actual needs, can filter out in the optimal classification number of cluster and the optimal of each cluster
The heart；
Step S210: the clustering distribution meeting default screening conditions according to filtering out carries out transfer storage facility addressing.
It is evidenced from the above discussion that, the present embodiment obtains the car load portfolio in each city default respectively, and acquisition meets pre-
If the city list of coordinates of the condition of acquisition；Using the car load portfolio corresponding with each city coordinate in this city list of coordinates as
Weight, is weighted weight respectively to each city coordinate in this city list of coordinates；To city coordinate row new after weighted
Each city coordinate in table carries out cluster analysis；The cluster meeting default screening conditions filtered out according to cluster analysis result
Distribution carries out transfer storage facility addressing, it is considered to the impact of city portfolio, can filter out the optimal classification number of cluster with each simultaneously
Transfer storage facility is set up at the optimal center of individual cluster, in time, material dispensing, the meaning weight such as map network planning, network optimization effectively
Greatly.
Transfer storage facility site selection system in one embodiment, as it is shown on figure 3, include:
Portfolio acquisition module 301, for obtaining the car load portfolio in each city default；
Coordinate obtaining module 302, presets acquisition for obtaining to meet according to the described car load portfolio presetting each city
The city list of coordinates of condition；
Weight increases module 303, for by car load portfolio corresponding for each city coordinate in the list of coordinates of described city
As weight, respectively each city coordinate in the list of coordinates of described city is weighted weight, obtains new city coordinate row
Table；
Cluster Analysis module 304, for carrying out cluster point to each city coordinate in described new city list of coordinates
Analysis, the clustering distribution under cluster number is preset in test；
Clustering distribution screening module 305, the clustering distribution under the default cluster number obtained according to test filters out
Meet the clustering distribution of default screening conditions；
Transfer storage facility addressing module 306, for carrying out transfer according to the clustering distribution meeting default screening conditions filtered out
Storehouse addressing.
As it is shown on figure 3, in a concrete example, described coordinate obtaining module 302 includes:
Portfolio comparing unit 3021, for respectively by the described car load portfolio presetting each city and pre-set business amount
Threshold value compares；
Coordinate acquiring unit 3022, for obtaining the car load portfolio city coordinate more than described pre-set business amount threshold value,
Obtain meeting the city list of coordinates of described default acquisition condition.
City portfolio, including influx and discharge, is to weigh logistics transportation networks to run and the important parameter of state,
City less to portfolio is rejected, and obtains the city coordinate that portfolio is many, is suitable for application.
Additionally, in a concrete example, each according in described new city list of coordinates of described default cluster number
The number of individual city coordinate is arranged.
The number of the newest each city coordinate in the list of coordinates of city is 10, and arranging and presetting cluster number is 4-
7, do not take the numerical value that two is less or bigger, the clustering distribution under test difference cluster number, result more corresponds to actual needs.
Additionally, in a concrete example, described clustering distribution includes several cluster centre coordinates and described new
The cluster ownership of each city coordinate in the list of coordinates of city.
After cluster analysis, we can obtain the cluster centre coordinates under different cluster number and each coordinate
Cluster ownership, for example with K-means clustering methodology, the clustering distribution under the conditions of test difference cluster number, K-means gathers
First alanysis method arbitrarily selects k object (city) as initial cluster center from n data object (city)；And for
Remaining other object (city), then according to them and the similarity (distance) of these cluster centres, assign these to respectively
(cluster centre representated by) cluster most like with it；Calculate each cluster centre (this cluster being obtained new cluster the most again
In the average of all objects)；Constantly repeat this process until canonical measure function starts convergence.
As it is shown on figure 3, in a concrete example, described clustering distribution screening module 305 includes:
Main engine plants' distance acquiring unit 3051, for obtaining each cluster centre to default main engine plants in each clustering distribution
Distance；
City distance acquiring unit 3052, is used in each clustering distribution according to each in described new city list of coordinates
The cluster ownership of individual city coordinate calculates each cluster centre distance to corresponding city；
Cost of transportation acquiring unit 3053, is used for according to cluster centre each in each clustering distribution to corresponding city
Distance, obtains each cluster centre cost of transportation to corresponding city；
Clustering distribution screening unit 3054, for according to cluster centre each in each clustering distribution to default main engine plants away from
From, each cluster centre to the distance in corresponding city, and each cluster centre is to the cost of transportation screening in corresponding city
Go out the clustering distribution meeting described default screening conditions.
Main engine plants are main port of shipments, obtain each cluster centre distance to default main engine plants in each clustering distribution,
According to the distance of each cluster centre to default main engine plants, obtain each cluster centre longest distance to default main engine plants, average departure
From, and beyond presetting main engine plants' number of main engine plants' distance；
According to the distance of each cluster centre to corresponding city, obtain the shortest to corresponding city of each cluster centre
Distance, longest distance, average distance and the city number beyond default city distance；According to each cluster centre to corresponding
The beeline in city obtains each cluster centre of each clustering distribution average beeline to corresponding city；In like manner root
The each cluster centre of each clustering distribution is obtained to corresponding according to the longest distance of each cluster centre to corresponding city
The average longest distance in city and maximum longest distance；Obtain to the average distance in corresponding city according to each cluster centre
To each cluster centre of each clustering distribution to corresponding city again average after average distance；
According to the distance of cluster centre each in each clustering distribution to corresponding city, and single kilometer of cost of transportation,
The average of haulage vehicle loads car load amount, obtains each cluster centre cost of transportation to corresponding city；
According to each cluster centre in above-mentioned each clustering distribution to the default distance of main engine plants, longest distance, average distance,
Beyond presetting main engine plants' number of main engine plants distances, the distance of each cluster centre to corresponding city, average beeline, put down
All longest distance, maximum longest distance, again average after average distance, beyond presetting the city number of city distance, with
And each cluster centre filters out the clustering distribution meeting default screening conditions to the cost of transportation in corresponding city, described preset
Screening conditions can be arranged according to actual needs, can filter out in the optimal classification number of cluster and the optimal of each cluster
The heart.
System based on the present embodiment shown in Fig. 3, a concrete work process can be discussed further below:
First portfolio acquisition module 301 obtains the car load portfolio presetting each city；Then coordinate obtaining module 302
In portfolio comparing unit 3021 respectively by described preset each city car load portfolio carry out with pre-set business amount threshold value
Relatively；Coordinate acquiring unit 3022 obtains the car load portfolio city coordinate more than described pre-set business amount threshold value, is met
The city list of coordinates of described default acquisition condition；Weight increases module 303 and is sat in each city in the list of coordinates of described city
The car load portfolio of mark correspondence, as weight, is weighted weight respectively to each city coordinate in the list of coordinates of described city,
Obtain new city list of coordinates；Each city coordinate in described new city list of coordinates is entered by Cluster Analysis module 304
Row cluster analysis, the clustering distribution under test default cluster number, described default cluster number is according to described new city coordinate
The number of each city coordinate in list is arranged, and described clustering distribution includes several cluster centre coordinates and described new
The cluster ownership of each city coordinate in the list of coordinates of city；Clustering distribution screening module 305, in main engine plants distance obtain
Unit 3051 obtains each cluster centre to the distance presetting main engine plants in each clustering distribution；City distance acquiring unit 3052
Each clustering distribution calculates in each cluster according to the cluster ownership of each city coordinate in described new city list of coordinates
The heart is to the distance in corresponding city；Cost of transportation acquiring unit 3053 according to cluster centre each in each clustering distribution to its
Distance to Yingcheng City, obtains each cluster centre cost of transportation to corresponding city；Clustering distribution screening unit 3054
According to cluster centre each in each clustering distribution to preset main engine plants distance, each cluster centre to the distance in corresponding city,
And each cluster centre filters out the clustering distribution meeting described default screening conditions to the cost of transportation in corresponding city；In
Stock relocation addressing module 306, for carrying out transfer storage facility addressing according to the clustering distribution meeting default screening conditions filtered out.
It is evidenced from the above discussion that, transfer storage facility site selection system of the present invention, it is considered to the impact of city portfolio, can screen simultaneously
Optimal center of the optimal classification number and each cluster that go out cluster carries out transfer storage facility addressing, in time, material dispensing effectively, right
Answer the network planning, the network optimization etc. significant.
Each technical characteristic of embodiment described above can combine arbitrarily, for making description succinct, not to above-mentioned reality
The all possible combination of each technical characteristic executed in example is all described, but, as long as the combination of these technical characteristics is not deposited
In contradiction, all it is considered to be the scope that this specification is recorded.
Embodiment described above only have expressed the several embodiments of the present invention, and it describes more concrete and detailed, but also
Can not therefore be construed as limiting the scope of the patent.It should be pointed out that, come for those of ordinary skill in the art
Saying, without departing from the inventive concept of the premise, it is also possible to make some deformation and improvement, these broadly fall into the protection of the present invention
Scope.Therefore, the protection domain of patent of the present invention should be as the criterion with claims.
Claims (10)
1. a transfer storage facility site selecting method, it is characterised in that comprise the following steps:
Obtain the car load portfolio presetting each city；
The city list of coordinates meeting default acquisition condition is obtained according to the described car load portfolio presetting each city；
Using car load portfolio corresponding for each city coordinate in the list of coordinates of described city as weight, respectively described city is sat
Each city coordinate in mark list is weighted weight, obtains new city list of coordinates；
Each city coordinate in described new city list of coordinates carries out cluster analysis, and gathering under cluster number is preset in test
Class is distributed；
The clustering distribution meeting default screening conditions is filtered out according to the clustering distribution under the default cluster number that test obtains；
The clustering distribution meeting default screening conditions according to filtering out carries out transfer storage facility addressing.
Transfer storage facility site selecting method the most according to claim 1, it is characterised in that according to the described car load presetting each city
Portfolio obtains the step of the city list of coordinates meeting default acquisition condition and includes:
Respectively the described car load portfolio presetting each city is compared with pre-set business amount threshold value；
Obtain the car load portfolio city coordinate more than described pre-set business amount threshold value, obtain meeting described default acquisition condition
City list of coordinates.
Transfer storage facility site selecting method the most according to claim 1, it is characterised in that described default cluster number according to described newly
City list of coordinates in each city coordinate number arrange.
Transfer storage facility site selecting method the most as claimed in any of claims 1 to 3, it is characterised in that described clustering distribution
Cluster including each city coordinate in several cluster centre coordinates and described new city list of coordinates belongs to.
Transfer storage facility site selecting method the most according to claim 4, it is characterised in that the default cluster number obtained according to test
Under clustering distribution filter out the step of the clustering distribution meeting default screening conditions and include:
Each cluster centre is obtained to the distance presetting main engine plants in each clustering distribution；
Each clustering distribution calculate each poly-according to the cluster ownership of each city coordinate in described new city list of coordinates
Class center is to the distance in corresponding city；
According to the distance of cluster centre each in each clustering distribution to corresponding city, obtain each cluster centre to corresponding
The cost of transportation in city；
According to the distance of cluster centre each in each clustering distribution to default main engine plants, each cluster centre is to corresponding city
Distance, and each cluster centre filters out to the cost of transportation in corresponding city and meets the cluster of described default screening conditions and divide
Cloth.
6. a transfer storage facility site selection system, it is characterised in that including:
Portfolio acquisition module, for obtaining the car load portfolio in each city default；
Coordinate obtaining module, for obtaining the city meeting default acquisition condition according to the described car load portfolio presetting each city
City's list of coordinates；
Weight increases module, is used for car load portfolio corresponding for each city coordinate in the list of coordinates of described city as power
Weight, is weighted weight respectively, obtains new city list of coordinates each city coordinate in the list of coordinates of described city；
Cluster Analysis module, for each city coordinate in described new city list of coordinates is carried out cluster analysis, test
Preset the clustering distribution under cluster number；
Clustering distribution screening module, for filter out according to the clustering distribution under the default cluster number that obtains of test meet default
The clustering distribution of screening conditions；
Transfer storage facility addressing module, for carrying out transfer storage facility addressing according to the clustering distribution meeting default screening conditions filtered out.
Transfer storage facility site selection system the most according to claim 6, it is characterised in that described coordinate obtaining module includes:
Portfolio comparing unit, for carrying out the described car load portfolio presetting each city with pre-set business amount threshold value respectively
Relatively；
Coordinate acquiring unit, for obtaining the car load portfolio city coordinate more than described pre-set business amount threshold value, is met
The city list of coordinates of described default acquisition condition.
Transfer storage facility site selection system the most according to claim 6, it is characterised in that described default cluster number according to described newly
City list of coordinates in each city coordinate number arrange.
9. according to the transfer storage facility site selection system described in any one in claim 6 to 8, it is characterised in that described clustering distribution
Cluster including each city coordinate in several cluster centre coordinates and described new city list of coordinates belongs to.
Transfer storage facility site selection system the most according to claim 9, it is characterised in that described clustering distribution screening module includes:
Main engine plants' distance acquiring unit, for obtaining each cluster centre to the distance presetting main engine plants in each clustering distribution；
City distance acquiring unit, for sitting according to each city in described new city list of coordinates in each clustering distribution
Target cluster ownership calculates each cluster centre distance to corresponding city；
Cost of transportation acquiring unit, for the distance according to cluster centre each in each clustering distribution to corresponding city,
To each cluster centre to the cost of transportation in corresponding city；
Clustering distribution screening unit, for the distance according to cluster centre each in each clustering distribution to default main engine plants, each poly-
Class center is to the distance in corresponding city, and each cluster centre filters out to the cost of transportation in corresponding city and meets institute
State the clustering distribution of default screening conditions.
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107590560A (en) * | 2017-09-04 | 2018-01-16 | 佛山佳牧乐科技有限公司 | The site selecting method and device of a kind of home-delivery center |
| CN107590560B (en) * | 2017-09-04 | 2020-09-22 | 佛山佳牧乐科技有限公司 | Site selection method and device for distribution center |
| CN108171452A (en) * | 2017-12-08 | 2018-06-15 | 苏宁云商集团股份有限公司 | A kind of express delivery point addressing method and device |
| CN108171452B (en) * | 2017-12-08 | 2022-04-05 | 苏宁易购集团股份有限公司 | Express delivery point addressing method and device |
| CN108833144A (en) * | 2018-05-30 | 2018-11-16 | 南京海兴电网技术有限公司 | A kind of intelligent electric meter concentrator site selecting method based on class statistic model |
| CN110175656A (en) * | 2019-06-04 | 2019-08-27 | 北京交通大学 | The city Clustering Model of raising train marshalling list efficiency based on group of cities heroin flow |
| CN110175656B (en) * | 2019-06-04 | 2021-08-31 | 北京交通大学 | An urban clustering model for improving train marshalling efficiency based on white goods flow in urban agglomerations |
| CN112651546A (en) * | 2020-12-10 | 2021-04-13 | 北京北大千方科技有限公司 | Bus route optimization method and system |
| CN112651546B (en) * | 2020-12-10 | 2024-07-16 | 北京北大千方科技有限公司 | Bus route optimization method and system |
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