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WO2018137330A1 - Procédé de traitement de commande, dispositif, serveur et support de stockage informatique - Google Patents

Procédé de traitement de commande, dispositif, serveur et support de stockage informatique Download PDF

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Publication number
WO2018137330A1
WO2018137330A1 PCT/CN2017/096000 CN2017096000W WO2018137330A1 WO 2018137330 A1 WO2018137330 A1 WO 2018137330A1 CN 2017096000 W CN2017096000 W CN 2017096000W WO 2018137330 A1 WO2018137330 A1 WO 2018137330A1
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Prior art keywords
order
group
orders
distance
cluster
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PCT/CN2017/096000
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English (en)
Chinese (zh)
Inventor
陈进清
徐明泉
黄绍建
咸珂
刘浪
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Beijing Xiaodu Information Technology Co Ltd
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Beijing Xiaodu Information Technology Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping
    • G06Q10/08355—Routing methods
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
    • G06Q10/083—Shipping
    • G06Q10/0838—Historical data
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0633—Managing shopping lists, e.g. compiling or processing purchase lists
    • G06Q30/0635—Managing shopping lists, e.g. compiling or processing purchase lists replenishment orders; recurring orders

Definitions

  • the present disclosure relates to the field of Internet technologies, and in particular, to an order processing method, apparatus, server, and computer storage medium.
  • O2O Online To Offline
  • a current logistics scheduling method is: for a logistics service provider, a plurality of distribution centers are preset in a city, and each distribution center corresponds to a certain coverage area, thereby, for any distribution center A
  • the delivery address that is, the order of the consignee's address within its coverage, will be dispatched to the distribution center A for distribution processing.
  • the dispatchers are often based on manual experience, and some orders that are close to the delivery address are assigned to the corresponding delivery personnel for distribution. This may result in a large number of orders that some delivery personnel need to deliver, and a small amount of orders delivered by some delivery personnel.
  • the distribution method based on manual experience may also result in the delivery address of the order assigned to a delivery person. It is closer in distance, so that the delivery personnel need to spend more time and travel longer distances to complete the delivery. Therefore, the current logistics scheduling method makes the utilization of distribution capacity low.
  • the embodiments of the present disclosure provide an order processing method, apparatus, server, and computer storage medium for improving the utilization rate of the delivery capacity.
  • an order processing method including:
  • the obtaining the actual packet capacity according to the total number of the multiple orders includes:
  • the actual packet capacity is determined according to the total number of the plurality of orders and the preset packet capacity such that the actual packet capacity is close to the preset packet capacity.
  • the preset packet capacity includes a preset minimum packet capacity and a preset maximum packet capacity.
  • Determining the actual packet capacity according to the total number of the multiple orders and the preset packet capacity, so that the actual packet capacity is close to the preset packet capacity including:
  • the actual packet capacity is obtained according to the following conditions, according to the total number of the multiple orders, the preset minimum packet capacity, and the preset maximum packet capacity:
  • the current cluster center order is selected according to the distance between the respective delivery addresses of the plurality of orders and the collection and delivery address, including:
  • Unscheduled orders are filtered out from the plurality of orders according to cluster state flags associated with each of the plurality of orders;
  • the clustering processing is performed on the un-clustered order according to the distance between the un-clustering order of the plurality of orders and the delivery address of the cluster center order, including:
  • the un-clustered order is clustered according to the distance between the un-cluster order of the plurality of orders and the delivery address of the order in the order group corresponding to the cluster center order.
  • the clustering is performed on the un-clustered order according to the distance between the delivery addresses of the orders in the order group corresponding to the clustering center order in the plurality of orders, including:
  • the clustering cutoff condition includes that the order quantity of the order group reaches the actual packet capacity.
  • an order processing apparatus including:
  • An obtaining module configured to obtain an actual packet capacity according to a total number of multiple orders, where the multiple orders correspond to the same collection and distribution address;
  • a selection module configured to select a current cluster center order according to a distance between a delivery address of the plurality of orders and the collection address;
  • a clustering processing module configured to cluster the un-clustered orders according to the actual grouping capacity according to a distance between an un-clustering order of the plurality of orders and a delivery address of the cluster center order, An order group corresponding to the cluster center order is determined.
  • the above-mentioned order processing apparatus includes a processor and a memory for storing a program supporting the order processing apparatus to execute the order processing method in the above first aspect, the processor being configured to use Executing the program stored in the memory.
  • the order processing device can also include a communication interface for the order processing device to communicate with other devices or communication networks.
  • an embodiment of the present disclosure provides a server, including a memory and a processor, where
  • the memory is configured to store one or more computer instructions, wherein the one or more computer instructions are for execution by the processor;
  • the processor is configured to: obtain an actual packet capacity according to a total number of multiple orders, where the multiple orders correspond to the same collection address; and select a current aggregation according to a distance between a delivery address of the plurality of orders and the collection address a class center order; based on the actual grouping capacity, clustering the unclustered orders according to a distance between an un-clustering order of the plurality of orders and a delivery address of the cluster center order to determine The order group corresponding to the cluster center order.
  • an embodiment of the present disclosure provides a computer storage medium for storing computer software instructions for use in an order processing apparatus, including a program for executing the order processing method in the first aspect described above.
  • the order processing method and apparatus when there are multiple orders in a certain distribution place and need to be distributed, firstly, the actual grouping capacity of each order group is adaptively determined according to the total order quantity, and then the actual grouping capacity is used as a constraint. , grouping multiple orders.
  • the current cluster center order is first selected based on the distance between the respective delivery addresses of the plurality of orders and the distribution address, and the cluster center order causes an order group, and further, according to the unscheduled orders in the plurality of orders
  • a plurality of un-clustered orders are clustered with the distance between the distribution addresses of the cluster center orders to obtain orders in the order group caused by the cluster center order, and an order group is formed.
  • the order within each group is based on the distance between the un-cluster order and the delivery address of the cluster center order.
  • the clustering determines that the distribution range of different groups is significantly different, the delivery address of the order within the same group has a strong agglomeration, and the group size is adapted to the order quantity, thereby ensuring that each delivery person is allocated.
  • the order group size is matched with the actual capacity and the distribution range is relatively concentrated. Overall, the utilization rate of the delivery capacity can be improved.
  • FIG. 1 is a flowchart of Embodiment 1 of an order processing method according to an embodiment of the present disclosure
  • Figure 1b - Figure 1f is a schematic diagram of a grouping process corresponding to the embodiment shown in Figure 1a;
  • Embodiment 2a is a flowchart of Embodiment 2 of an order processing method according to an embodiment of the present disclosure
  • FIG. 2b-2c is a schematic diagram of an order replenishment process corresponding to the embodiment shown in FIG. 2a;
  • FIG. 3 is a flowchart of Embodiment 3 of an order processing method according to an embodiment of the present disclosure
  • 3b-3d are schematic diagrams of an order replenishment process corresponding to the embodiment shown in FIG. 3a;
  • Embodiment 4a is a flowchart of Embodiment 4 of an order processing method according to an embodiment of the present disclosure
  • 4b-4d are schematic diagrams of an order adjustment process corresponding to the embodiment shown in FIG. 4a;
  • FIG. 5 is a flowchart of Embodiment 5 of an order processing method according to an embodiment of the present disclosure
  • FIG. 6 is a schematic structural diagram of Embodiment 1 of an order processing apparatus according to an embodiment of the present disclosure
  • FIG. 7 is a schematic structural diagram of Embodiment 2 of an order processing apparatus according to an embodiment of the present disclosure.
  • FIG. 8 is a schematic structural diagram of Embodiment 3 of an order processing apparatus according to an embodiment of the present disclosure.
  • FIG. 9 is a schematic structural diagram of Embodiment 4 of an order processing apparatus according to an embodiment of the present disclosure.
  • FIG. 10 is a schematic structural diagram of Embodiment 5 of an order processing apparatus according to an embodiment of the present disclosure.
  • FIG. 11 is a schematic structural diagram of Embodiment 6 of an order processing apparatus according to an embodiment of the present disclosure.
  • first, second, third, etc. may be used to describe XXX in embodiments of the present disclosure, these XXX should not be limited to these terms. These terms are only used to distinguish XXX.
  • the first XXX may also be referred to as a second XXX without departing from the scope of the embodiments of the present disclosure.
  • the second XXX may also be referred to as a first XXX.
  • the words “if” and “if” as used herein may be interpreted to mean “when” or “when” or “in response to determining” or “in response to detecting.”
  • the phrase “if determined” or “if detected (conditions or events stated)” may be interpreted as “when determined” or “in response to determination” or “when detected (stated condition or event) “Time” or “in response to a test (condition or event stated)”.
  • FIG. 1 is a flowchart of Embodiment 1 of an order processing method according to an embodiment of the present disclosure.
  • the order processing method provided by this embodiment may be executed by an order processing apparatus, and the order processing apparatus may be implemented as software or implemented as software.
  • the order processing device can be integrated in a device on the side of the logistics dispatch platform, such as a server. As shown in FIG. 1a, the method includes the following steps:
  • cluster the un-clustered orders according to the distance between the un-cluster order of the plurality of orders and the delivery address of the cluster center order to determine an order group corresponding to the cluster center order.
  • the order in the embodiment of the present disclosure may be a courier order.
  • the courier order will experience at least one distribution center, so that when a certain distribution center is reached, the order will be associated with the collection address. Therefore, for a collection and distribution address, based on this, an order corresponding to the collection and delivery address can be obtained, and the total number of the plurality of orders is the total number of orders corresponding to the collection and delivery address in a certain period of time.
  • the order corresponding to each of the collection and distribution addresses may be counted at a certain time interval, thereby obtaining a plurality of orders to be allocated corresponding to the same collection and distribution address, and in the following embodiments of the present disclosure, only one
  • the order processing method is described by taking a plurality of orders corresponding to the collection and delivery addresses as an example.
  • the actual number of orders for each order group is determined in real time in accordance with the current order quantity.
  • the correspondence between the order quantity interval and the actual packet capacity may be preset, so that the actual packet capacity currently used is determined based on the correspondence relationship and the interval in which the current order quantity is located.
  • the obtaining of the actual packet capacity may be implemented as follows:
  • the actual packet capacity is determined based on the total number of multiple orders and the preset packet capacity such that the actual packet capacity is close to the preset packet capacity.
  • the preset packet capacity may include a preset minimum packet capacity and a preset maximum packet capacity, that is, a packet capacity interval is formed by the preset minimum packet capacity and the preset maximum packet capacity, thereby, in a specific
  • the actual packet capacity may be obtained according to the total number of multiple orders, the preset minimum packet capacity, and the preset maximum packet capacity, by combining the following conditions: the remainder of dividing the total number of multiple orders by the actual packet capacity is greater than the preset minimum packet. Capacity, where the actual packet capacity is an integer taken between the preset minimum packet capacity and the preset maximum packet capacity.
  • the upper and lower limits of the capacity of any order group may be preset, and the actual packet capacity is taken from the upper and lower limits.
  • the total number of the above multiple orders is divided by the remainder of the actual grouping capacity, that is, the total number of orders is modulo the actual grouping capacity.
  • the actual packet capacity may be a minimum capacity value such that the remainder is greater than the minimum packet capacity, that is, assuming that a plurality of capacity values between the upper and lower limits of the capacity can satisfy the condition, a minimum capacity value that satisfies the condition is taken.
  • the practical significance of the above conditions is that the total number of orders for the above multiple orders is likely not to be an integral multiple of the actual grouping capacity, that is, the multiple orders are often not evenly divided into n order groups.
  • the above-mentioned remainder is as large as possible to be greater than the minimum packet capacity, in order to obtain as many order orders as possible in the order group obtained from the plurality of orders in sequence according to the actual packet capacity, so as to be effective for the delivery capacity.
  • the use has a positive effect, because it can make the order quantity of each distribution personnel to be balanced to a certain extent, avoiding the imbalance of the amount of orders received by some distribution personnel and the unbalanced load of some distribution personnel.
  • the preset packet capacity may be determined by assuming that the delivery tools of the respective delivery personnel are the same, that is, each delivery tool has the same transportation capability, such as having the same volume size, and capable of carrying the total
  • the weight is the same.
  • the corresponding number of items to be delivered, the weight of the item, the volume of the item, and the like are extracted, and then the distribution is determined according to the total weight of the delivery tool, such as the upper limit of the weight of the delivery tool.
  • the average order quantity that the tool can carry which can be used as a preset grouping capacity.
  • the final preset packet capacity may be expressed differently. For example, in addition to determining the average order quantity that the delivery tool can carry, it is also possible to statistically determine the minimum order quantity that the delivery tool can carry, and the maximum number.
  • the order quantity is the above minimum packet capacity and maximum packet capacity.
  • each order group obtained by the final grouping in the embodiment of the present disclosure may have the same packet capacity, that is, have the actual packet capacity determined above, but may also be that each order group may have different packets.
  • Capacity such as the packet capacity of one or several order groups, is the result of fine-tuning based on the actual packet capacity. For example, for an order group, the fine-tuning of the grouping capacity is based on the following: when the order group is generated, it is found that the order capacity in the order group has not reached the limit of the actual packet capacity, the order The total weight and/or total volume corresponding to the order within the group has reached the limit of the weight and/or volume of the delivery tool.
  • the packet capacity within the order group will be less than the actual packet capacity limit; conversely, if found
  • the order capacity in the order group has reached the above limit of the actual grouping capacity, the total weight and/or the total volume corresponding to the order in the order group has not reached the limit of the weight and/or volume of the delivery tool.
  • the packet capacity within the order group can exceed the limit of the actual packet capacity.
  • the actual packet capacity in this embodiment can be understood as an estimated value.
  • the order capacity of each order group may be floating based on the estimated value.
  • the overall idea of grouping multiple orders is: a division generation process for each order group: first selecting a cluster center order from the cluster The central order leads to an order group; further, based on the cluster center order, the order is continuously added to the order group, that is, the cluster processing in the order group is performed until the order group satisfies the above-mentioned actual grouping capacity limit, or Meet the clustering cutoff criteria for other order groups. After that, the division generation process of the next order group is triggered until the above multiple orders are grouped.
  • the selection basis of the cluster center order is selected according to the distance between the delivery address of the order and the collection and distribution address.
  • the order for joining the order in the above order group is based on the distance between the delivery addresses between the unclustered order and the cluster center order.
  • the order of the order in the order group that is drawn may be based on the delivery address of the other order that has not been clustered to an order group and the order of the cluster center. Select between the delivery addresses between the delivery addresses; in addition, further based on the delivery addresses of these other orders that have not been clustered to an order group and the order groups that have been clustered to the cluster center order The distance between the delivery addresses of the orders within the selection is to be described in detail later.
  • the distance between the un-cluster order of the plurality of orders corresponding to the collection address and the delivery address of the cluster center order may be The order is clustered to determine the order group corresponding to the cluster center order; in another alternative, the delivery address of the order in the order group corresponding to the unclustered order and the cluster center order in the plurality of orders may be Inter-distance, clustering un-cluster orders.
  • the un-cluster order refers to each of the plurality of orders that have not been clustered into an order group.
  • the proximity from the collection address to the remote collection address may be And the far way to select the cluster center order in turn, or to select the cluster center order in turn from the far and near way from the collection address to the collection address.
  • one or more cluster center orders may be selected at one time, for example, two cluster center orders are selected at a time.
  • the distribution of the plurality of cluster center orders The addresses should be far apart from each other. Therefore, in practical applications, the distance threshold between the delivery addresses of different cluster center orders can be reasonably set to make reasonable selection of different cluster center orders.
  • the cluster status flag associated with each of the current orders may be firstly selected to filter out the multiple orders.
  • the class order, and further, according to the distance between the respective delivery addresses of the un-cluster orders and the collection and distribution addresses, the orders farthest from the collection and distribution addresses are selected from the un-cluster orders as the current cluster center order.
  • the distance matrix reflecting the distance between the distribution address and the delivery address of each order may be constructed in advance. Therefore, for the first order group, an order can be selected from the distance matrix as the first cluster center order, for example, the order corresponding to the maximum distance value is used as the first cluster center order, and then the The aggregation process of the order in the first order group corresponding to the first cluster center order. And, in the process, optionally, the added order may be marked as clustered each time an order is determined to join the first order group.
  • the distance value of the unmarked, un-clustered order and the cluster center order can be filtered from the distance matrix based on the mark. And then determine the second cluster center order, for example, the order corresponding to the maximum distance value as the second cluster center order.
  • the selection process of subsequent cluster center orders is similar, and will not be described again.
  • the delivery address of order a is farthest from the collection address, so the current order a is currently selected as the cluster center order, and it is assumed that the order group led by the cluster center order a is represented as order group 1. Next, the order clustering process for order group 1 needs to be performed.
  • the order may be constructed for each order in advance.
  • the distance matrix between the corresponding delivery addresses For an order, the meaning of the distance matrix between the corresponding delivery addresses is: the distance between the delivery address of the order and the delivery address of the other order, that is, the distance between the delivery addresses, so as to be followed by the distance matrix between the delivery addresses.
  • Clustering processing each element in the distance matrix of each order's delivery address, that is, each distance value, may also be associated with a cluster status flag. If the corresponding order has been clustered to an order group, the flag is set to The cluster status indicator is set, otherwise, it is set to the uncluster status indicator.
  • the cluster processing mode of the order group corresponding to the order based on the distance matrix between the delivery addresses corresponding to the cluster center order, and the cluster state flag associated with each distance value in the combination matrix, it can be known that the current un-cluster orders are relative The distance between the delivery addresses of the cluster center order; further, the actual grouping capacity is the order quantity constraint in the order group, and the n orders with the largest distance value selected from the ungrouped orders are added to the order group, n is taken The value is the actual packet size minus one.
  • the order group corresponding to the cluster center order is generated.
  • the shipping address of the cluster center order a can be used.
  • select from the other orders b, c, d, e, f the two orders whose delivery address is closest to the delivery address of the cluster center order a assuming that the order b, c is added to the order group 1, and thus, the order Group 1 includes three orders order a, b, and c.
  • the timing of constructing the distance matrix between delivery addresses corresponding to the above-mentioned order is not limited to the initial situation of the foregoing example, and the distance between the delivery addresses between the order and other orders is not limited to one time.
  • the calculation is completed.
  • the cluster center order leads to an order group, and constructs a distance matrix between delivery addresses corresponding to the cluster center order, so as to select one or more to join the order group based on the matrix.
  • the distance matrix between the delivery addresses corresponding to the order just joined to the order group can be reconstructed at this time, and at this time, the order is just added.
  • the distance matrix between the delivery addresses corresponding to the group order may only include the distance between the delivery address and the delivery address of the un-cluster order, and the distance between the delivery address and the delivery address of the order in the order group may not be calculated.
  • the embodiment of the present disclosure further provides another optional method for clustering the order in the order group, that is, the un-cluster order and the cluster center order according to the plurality of orders mentioned above.
  • the distance between the delivery addresses of the orders in the corresponding order group is clustered for the un-clustered orders.
  • the specific process can be:
  • the order that is closest to the order group is selected from the current un-cluster order
  • the clustering cutoff condition includes: the number of orders of the current order group reaches the actual packet capacity.
  • the order closest to the order group refers to the unscheduled order with the shortest distance between the delivery addresses among the plurality of un-clustered orders that are closest to the delivery address of each order in the order group.
  • order group 1 contains only order a. Since all other orders are currently in an un-clustering state, that is, they are all un-clustered orders, they can be selected from the current un-clustering orders b, c, d, e, and f based on the distance matrix between the delivery addresses of order a.
  • the order closest to order a that is, the order closest to the current order group 1.
  • the selected nearest order relative to the current order group is referred to as an order to be aggregated, indicating the meaning of the order waiting to be aggregated into the current order group.
  • the order can be selected from the un-cluster order.
  • the cluster status flag of the order b becomes the clustered state, and after the ungrouped order is updated, the unclustered order becomes the order c, d, e, f.
  • the number of orders in the current order group 1 has reached the actual grouping capacity 3. Since the current order group 1 includes only orders a and b, and has not yet reached 3 orders, the next iteration process is performed.
  • the current order group 1 includes orders a and b, and the current un-cluster order includes orders c, d, e, f.
  • the current un-cluster order includes orders c, d, e, f.
  • the order a in 1 determines the closest un-clustering distance between the delivery address and the delivery address of the order a from the current un-clustered orders c, d, e, and f based on the distance matrix between the corresponding delivery addresses.
  • Order assuming that the distance between the delivery address of order c and the delivery address of order a is smaller than the delivery addresses of other un-clustered orders, ie, d, e, and f, respectively.
  • the distance between the delivery addresses of a determines that the order c is the closest order to the order a.
  • the current un-cluster order c, d, e, f is determined between the delivery address and the delivery address of the order b.
  • the distance from the nearest un-clustered order assuming that the distance between the delivery address of order d and the delivery address of order b is less than the delivery address of other un-clustered orders, ie, c, e, f, and the delivery address of order b Distance determines that order d is the closest order to order b. Then, at this time, for the current order group 1, the orders c, d constitute a candidate order set, and the closest to-order order with respect to the current order group 1 is to select the to-be-integrated order from the candidate order set. , joined to order group 1.
  • the order of the order that is closest to the current order group 1 to be aggregated is based on: the order corresponding to the minimum distance between the shortest delivery addresses corresponding to each order in the current order group 1 is the latest relative to the current order group 1 The order will also be placed in the order.
  • the distance between the shortest delivery addresses is relative to the order.
  • the distance between the shortest delivery addresses corresponding to an order refers to: the delivery address of the order and the current delivery address of each un-cluster order.
  • the shortest distance between the distances For example, for the order a in the current order group 1, the ungrouped order c, d, e, f, the distance between the delivery address of the order c and the delivery address of the order a compared to the orders d, e, f The shortest, so it is called the shortest delivery address distance.
  • the minimum of the distance between the shortest delivery addresses is for the order group.
  • each order included in the current order group has a shortest delivery address distance, and the minimum value refers to these shortest delivery addresses.
  • the minimum of the distances between For the order group 1 in the above example, since the order quantity in the current order group 1 is not 1, that is, for each of the orders, there is a shortest delivery address distance corresponding thereto, and the distance between all the shortest delivery addresses is The unclustered order corresponding to the minimum value is the current order to be aggregated into the order group, that is, the order closest to the current order group.
  • the distance between the order a and the shortest delivery address of the order c is D1
  • the distance between the shortest delivery address of the order b and the order d is D2
  • D1 is less than D2
  • the order c is the current to-be-integrated order, and Join in order group 1, as shown in Figure 1d.
  • the cluster status flag of the order c becomes the clustered state
  • the un-cluster order becomes the order d, e, and f.
  • the order a is used as the cluster center order.
  • Order group 1 is grouped.
  • the un-cluster order is the order d, e, f. It should be noted that if the actual packet capacity is assumed to be 4, then for the order group 1, the current order group 1 includes orders a, b, and c, and has not reached the capacity limit of 4 orders, and then continues to execute.
  • An iterative process, the third iteration process is similar to the second iteration process.
  • the next cluster center order selection can be made, and the order clustering process of the order group 2 led by the following cluster center order is as shown in FIG. 1e, assuming that the current cluster is not clustered. If the order is order d, e, f, then according to these un-cluster orders and the collection address The distance from which the order farthest from the collection address is d is selected, and the order d is taken as the second cluster center order, and the order group 2 is drawn. Further, referring to the foregoing description of the process of clustering orders to the order group 1, the order is continuously added to the order group 2, assuming that the cluster cutoff condition is that the number of orders in the order group reaches the actual grouping capacity 3, as shown in FIG. 1f, Order group 2 includes three orders d, e, and f. At this point, all orders have been grouped.
  • the latest order with respect to an order group or an order set mentioned in the following embodiments may be determined according to the following manner: first, corresponding to each order in the group/set The minimum distance value of the un-cluster state flag is determined in the distance matrix between the delivery addresses, and then the determined minimum distance values are compared, and the minimum value is selected, that is, the minimum value is selected from the plurality of minimum distance values, The unclustered order corresponding to the minimum value is the nearest order to which the group/set currently corresponds.
  • the clustering cutoff condition may be that the number of orders in the order group reaches the actual grouping capacity limit, so that all the finally obtained order groups have a relatively balanced order capacity.
  • the clustering cutoff condition may further include: selecting a closest distance of the order to be aggregated into the order group relative to the order group is greater than or equal to a preset distance threshold. This condition further ensures that the orders within the same order group are relatively concentrated in the spatial scope, avoiding the need for the delivery personnel to complete the delivery of a set of orders within an excessively wide range.
  • the order that has been selected is the order c
  • the distance between the order c and the delivery address of the order a is D1
  • D1 is greater than or equal to the preset distance threshold
  • the order c is far from the order in the order group 1.
  • the order c is not added to the order group 1, then the order group 1 will eventually only include the orders a, b, and the order number does not reach the actual group size.
  • the distance threshold can be set reasonably to make a compromise between the order group capacity and the spatial range concentration.
  • the actual grouping capacity of each order group is adaptively determined according to the total order quantity, and then the actual grouping capacity is used as a constraint, and multiple Orders are grouped.
  • the current cluster center order is first selected based on the distance between the respective delivery addresses of the plurality of orders and the distribution address, and the cluster center order causes an order group, and further, according to the unscheduled orders in the plurality of orders
  • the un-cluster order is clustered with the distance between the delivery addresses of the cluster center order to obtain the order in the order group caused by the cluster center order, and an order group is formed.
  • the order within each group is based on the distance between the un-cluster order and the delivery address of the cluster center order.
  • the clustering determines that the distribution range of different groups is significantly different, the delivery address of the order within the same group has a strong agglomeration, and the group size is adapted to the order quantity, thereby ensuring that each delivery person is allocated.
  • the order group size is matched with the actual capacity and the distribution range is relatively concentrated. Overall, the utilization rate of the delivery capacity can be improved.
  • the embodiment of the present disclosure further provides an additional means for replenishing the order.
  • the premise of the supplementary order is based on whether the actual determined packet capacity has reached the preset maximum packet capacity, because in actual application, the maximum packet capacity is often comprehensive statistics, considering various factors affecting the utilization of the delivery capacity. If the actual packet capacity is less than the preset maximum packet capacity, it indicates that for the current order group 1, a certain number of unclustered orders satisfying certain conditions can be appropriately added. That is, if the actual packet capacity is less than the preset maximum packet capacity, the order may be replenished to the current order group according to the distance between the current order group order and the current un-cluster order delivery address. Of course, if there is no order in the current un-cluster order that satisfies the certain condition, the order group 1 can be replenished.
  • one or more iterative processes may be performed to sequentially replenish the order group 1 with an order that satisfies certain conditions, and ideally, it is uniformly added to Until the supplementary deadline is met.
  • FIG. 2a is a flowchart of a second embodiment of an order processing method according to an embodiment of the present disclosure. As shown in FIG. 2a, after performing a 103, the following steps may be further included:
  • the to-be-replenished order that is the closest to the order group distance in the un-cluster order refers to the distance between the delivery addresses in the plurality of un-clustered orders that are closest to the delivery address of each order in the order group.
  • the shortest un-cluster order refers to the distance between the delivery addresses in the plurality of un-clustered orders that are closest to the delivery address of each order in the order group.
  • order group 1 has been currently grouped, wherein order group 1 contains orders a, b, and c.
  • the current un-cluster order is order d, e, f.
  • order d is the order closest to the order group 1, that is, the order to be replenished.
  • the order with the closest distance between the delivery address and the delivery address of order a is order d, and the distance between the delivery address of order a and order d is assumed to be D1; the delivery address and the order b
  • the closest order between the delivery addresses is order e, and the distance between the delivery address of the order b and the order e is assumed to be D2; the order closest to the delivery address of the delivery address and the delivery address of the order c is the order f, and the order c and the order f are assumed.
  • the distance between the delivery addresses is D3, and it is assumed that D1 is the smallest among D1, D2, and D3.
  • the order d is the closest order to be replenished relative to the current order group 1, and the closest distance to the order group 1 is D1.
  • the closest distance of the to-be-replenished order relative to the remaining un-clustered order set refers to the distance between the to-be-supplemented order and the delivery address of each un-clustered order in the remaining un-clustered order set.
  • the shortest distance For example, after determining the order d closest to the order group 1 from the current un-cluster orders d, e, f, the remaining un-cluster orders e, f can be regarded as a whole to constitute the remaining un-cluster Order collection. Further, the nearest distance between the order d and the remaining un-clustered order set is determined by calculating the distance between the order d and the delivery address corresponding to the orders e and f in the set respectively.
  • D4 the distance between the order d and the delivery address of the order e is D4
  • D5 the distance between the order d and the delivery address of the order f is D5. If D4 is less than D5, it is determined that D4 is the closest distance of the order d to the remaining un-clustered order set.
  • the closest distance of the to-be-replenished order relative to the order group is the shortest distance between the to-be-replenished order and the delivery address of each order in the order group.
  • the order replenishment process is an iterative process
  • the supplemental cut-off condition of the iteration includes: the order quantity of the order group reaches the preset maximum packet capacity, or the closest distance of the to-be-replenished order relative to the order group is greater than or Equal to the closest distance of the order to be replenished relative to the remaining unclustered order set.
  • the distance D1 between the order d and the delivery address of the order a and the distance D4 between the order d and the delivery address of the order e are compared. If D1 is less than D4, the order d is added to the order group 1, as shown in Fig. 2c. As shown, at this time, the order in order group 1 is a, b, c, d. When an un-cluster order is updated, the current un-cluster order is updated to: order e, f.
  • the process ends, and the final order group 1 is obtained; if the number of orders in the order group 1 has not reached the preset maximum grouping capacity at this time, The selection of the next order to be replenished is made, and the selection method is the same as the selection method of the order d, and will not be described.
  • FIG. 3 is a flowchart of a third embodiment of an order processing method according to an embodiment of the present disclosure. As shown in FIG. 3a, after performing a 103, the following steps may be further included:
  • the to-be-replenished order closest to the order group distance refers to an un-clustered order with the shortest distance between the delivery addresses in the distance from the delivery address of each order in the order group.
  • the closest distance of the to-be-replenished order relative to the replenishment order set is the shortest distance among the distances between the replenishment order and the delivery address of each replenishment order in the replenishment order set.
  • the closest distance of the to-be-replenished order relative to the order group refers to the shortest distance between the replenishment order and the delivery address of each order in the order group.
  • updating the un-clustered order may be to modify the identity of the un-clustered order that is added to the order group to a clustered order to remove the un-clustered order that is added to the order group from the un-cluster order set.
  • the order replenishment process is an iterative process
  • the supplemental cut-off condition of the iteration includes: the order quantity of the order group reaches the preset maximum packet capacity, or the closest distance of the to-be-replenished order relative to the order group is greater than or Equal to the closest distance of the replenishment order relative to the replenishment order set.
  • a supplementary order set is first generated, and initially, the supplementary order set is empty.
  • the order in the current order group 1 is the order a, b, c, and the current un-cluster order includes the orders d, e, f.
  • the order selection method provided in the foregoing embodiment it is assumed that the order d is the order closest to the order group 1, that is, the current order to be replenished, and it is assumed that the closest distance of the order d to the order group 1 is D1.
  • the current distance of the current to-be-replenished order d relative to the supplementary order set may be considered to be infinite, and at this time, the order to be replenished is relative to the order group 1.
  • the nearest distance is less than the closest distance to its relative replenishment order set, the order to be replenished is added to order group 1, and the order to be replenished is added to the replenishment order set, as shown in Figure 3b.
  • the un-cluster order is updated, and the updated un-cluster order is the order e, f.
  • the current order group 1 includes orders a, b, c, and d. If the number of orders in the group has not reached the preset maximum packet capacity, the selection process of the next to-be-replenished order is iteratively executed.
  • the to-be-replenished order corresponding to the current order group 1 including the orders a, b, c, and d is first selected from the current un-clustering orders e and f, assuming that the order e is selected as the current The order to be replenished, and the closest distance of the order e to the current order group 1 is assumed to be D2.
  • the nearest distance of the order e relative to the supplementary order set is determined, since only the order d is included in the current supplementary order set, Therefore, at this time, the closest distance is the distance between the order e of the order e and the order d, which is assumed to be D3.
  • the distance between the delivery addresses of each order in the supplementary order and the supplementary order set is respectively calculated, and the shortest distance between the delivery addresses is selected as the to-be-replenished. The closest distance of the order relative to the replenishment order set.
  • the sizes of D2 and D3 are compared. If D2 is smaller than D3, the order to be replenished is added to the order group 1, and the order to be replenished e is added to the supplementary order set, as shown in FIG. 3d. On the other hand, if D2 is smaller than D3, the order to be replenished e is discarded, and the grouping processing of the order group 1 is ended.
  • the order replenishing means of the embodiment shown in FIG. 2a and FIG. 3a After the order grouping process is performed in the order group with the actual packet capacity as the limit, after the order group is obtained, if the actual packet capacity has not reached the maximum packet capacity limit, Further, the order with the obvious concentration in the space within the order group can be further added to the order group, so that each delivery person can deliver more orders at a time, which can further improve the utilization rate of the delivery capacity. .
  • the order of the order in the order group can be adjusted according to the distance between the order in the order group and the delivery address of the order in the other order group.
  • the adjustment process can be implemented in conjunction with the embodiment shown in Figure 4a.
  • FIG. 4A is a flowchart of a fourth embodiment of an order processing method according to an embodiment of the present disclosure. As shown in FIG. 4a, optionally, after performing group processing on multiple orders corresponding to the current collection and delivery address, the method may further include The following steps:
  • first closest distance is greater than the second closest distance, add any one of the orders to another order group to which the order corresponding to the second closest distance belongs.
  • the first closest distance of the any order relative to other orders in the order group refers to the shortest distance between the delivery addresses between the any order and other orders in the order group.
  • the second closest distance of any one of the orders relative to the order in the other order group is the shortest distance between the delivery address between the order and the order between each order in the other order group.
  • the order in order group 1 includes orders a, b, and c.
  • the order in order group 2 includes orders d, e, and f.
  • any order c in order group 1 calculate it separately.
  • the distance between the delivery addresses with other orders in order group 1, that is, orders a and b, is assumed to be D1 and D2, respectively.
  • the minimum distance between delivery addresses is selected from D1, D2 as the first closest distance of the order c relative to other orders in the order group 1, and if D1 is less than D2, it is determined that the first closest distance is D1, as shown in Fig. 4c. It can be understood that, for the orders a and b in the order group 1, the calculation manner is the same as the calculation method of the order c, and will not be described again.
  • the distance between the delivery address between the order c and each order group other than the order group 1, that is, the order in the order group 2, is calculated separately, assuming that the distance between the order of the order c and the order d is D3, the order c
  • the distance between the delivery address and the order e is D4
  • the distance between the delivery address between the order c and the order f is D5.
  • the ownership of the order is adjusted according to the closest distance of the order relative to the currently owned order group and the closest distance of the order relative to other order groups, so as to ensure the order in the same order group.
  • orders of different order groups have more obvious positional dispersion, so as to avoid the same delivery personnel need to walk more ways to complete the distribution of an order group and improve the utilization of distribution capacity.
  • FIG. 5 is a flowchart of Embodiment 5 of an order processing method according to an embodiment of the present disclosure. As shown in FIG. 5, after 103, the following steps may be further included:
  • the delivery of the orders can also be performed for each order group.
  • the process performs navigation path planning.
  • the principle of navigation path planning can be the shortest path principle.
  • the corresponding navigation path can be planned according to the minimum principle of the total path.
  • order processing apparatus of one or more embodiments of the present disclosure will be described in detail below.
  • order processing devices can be implemented in the infrastructure of the server or in an interactive architecture between the client and the server.
  • order processing devices can be constructed using commercially available hardware components configured by the steps taught by the present solution.
  • FIG. 6 is a schematic structural diagram of Embodiment 1 of an order processing apparatus according to an embodiment of the present disclosure. As shown in FIG. 6, the apparatus includes: an obtaining module 11, a selecting module 12, and a clustering processing module 13.
  • the obtaining module 11 is configured to obtain an actual packet capacity according to a total number of the plurality of orders, where the plurality of orders correspond to the same collection and distribution address.
  • the selecting module 12 is configured to select a current cluster center order according to a distance between a delivery address of the plurality of orders and the collection address.
  • the clustering processing module 13 is configured to cluster the un-clustered orders according to the actual grouping capacity according to the distance between the un-clustering order of the plurality of orders and the delivery address of the cluster center order To determine an order group corresponding to the cluster center order.
  • the cluster processing module 13 is specifically configured to: according to the actual packet capacity, according to the distance between the delivery addresses of the orders in the order group corresponding to the clustered center order in the unscheduled order of the plurality of orders And clustering the un-cluster order to determine an order group corresponding to the cluster center order.
  • the obtaining module 11 is specifically configured to:
  • the actual packet capacity is determined according to the total number of the plurality of orders and the preset packet capacity such that the actual packet capacity is close to the preset packet capacity.
  • the obtaining module 11 is specifically configured to:
  • the actual packet capacity is obtained according to the following conditions, according to the total number of the multiple orders, the preset minimum packet capacity, and the preset maximum packet capacity:
  • An integer between the preset packet capacity includes the preset minimum packet capacity and the preset maximum packet capacity.
  • the selection module 12 includes: a first selection unit 121 and a second selection unit 122.
  • the first selecting unit 121 is configured to filter an un-clustered order from the plurality of orders according to a cluster state flag associated with each of the plurality of orders.
  • a second selecting unit 122 configured to select, according to a distance between a delivery address of the un-cluster order and the collection address, an order that is farthest or closest to the collection address from the un-cluster order The cluster center order.
  • the cluster processing module 13 is specifically configured to:
  • the clustering cutoff condition includes that the order quantity of the order group reaches the actual packet capacity.
  • the clustering cutoff condition further includes: a closest distance of the selected order relative to the order group is greater than or equal to a preset distance threshold.
  • the apparatus shown in FIG. 6 can perform the method of the embodiment shown in FIG. 1a.
  • the apparatus shown in FIG. 6 can perform the method of the embodiment shown in FIG. 1a.
  • the parts not described in detail in this embodiment reference may be made to the related description of the embodiment shown in FIG. 1a.
  • the implementation process and technical effects of the technical solution refer to the description in the embodiment shown in FIG. 1a, and details are not described herein again.
  • FIG. 7 is a schematic structural diagram of Embodiment 2 of an order processing apparatus according to an embodiment of the present disclosure. As shown in FIG. 7, on the basis of the embodiment shown in FIG. 6, the apparatus further includes: a supplementary processing module 21.
  • the supplementary processing module 21 is configured to, if the actual packet capacity is less than the preset maximum packet capacity, replenish the order group according to the distance between the current order group order and the current un-cluster order delivery address.
  • the supplementary processing module 21 may include a first supplementary processing unit 211, configured to:
  • the to-be-replenished order is added to the order group
  • the supplementary deadline condition includes: the order quantity of the order group reaches the preset maximum packet capacity, or the closest distance of the to-be-replenished order relative to the order group is greater than or equal to the to-be-replenished order relative to the remaining The closest distance to the ungrouped order collection.
  • the apparatus shown in FIG. 7 can perform the method of the embodiment shown in FIG. 2a.
  • the apparatus shown in FIG. 7 can perform the method of the embodiment shown in FIG. 2a.
  • the parts not described in detail in this embodiment reference may be made to the related description of the embodiment shown in FIG. 2a.
  • the implementation process and technical effects of the technical solution refer to the description in the embodiment shown in FIG. 2a, and details are not described herein again.
  • FIG. 8 is a schematic structural diagram of Embodiment 3 of an order processing apparatus according to an embodiment of the present disclosure.
  • the supplementary processing module 21 may further include: Supplementation processing unit 212.
  • the second supplementary processing unit 212 is configured to:
  • the to-be-replenished order is added to the order group, and the to-be-replenished order is added to the supplementary order set;
  • the supplementary deadline condition includes: the order quantity of the order group reaches the preset maximum group size, or the closest distance of the to-be-replenished order relative to the order group is greater than or equal to the to-be-replenished order relative to the supplement The closest distance to the order collection.
  • the apparatus shown in FIG. 8 can perform the method of the embodiment shown in FIG. 3a.
  • the apparatus shown in FIG. 8 can perform the method of the embodiment shown in FIG. 3a.
  • the parts not described in detail in this embodiment reference may be made to the related description of the embodiment shown in FIG. 3a.
  • the implementation process and technical effects of the technical solution refer to the description in the embodiment shown in FIG. 3a, and details are not described herein again.
  • FIG. 9 is a schematic structural diagram of Embodiment 4 of an order processing apparatus according to an embodiment of the present disclosure. As shown in FIG. 9 , on the basis of the embodiment shown in FIG. 6 , the apparatus further includes: an adjustment module 41 .
  • An adjustment module 41 configured to deliver the order according to the order group and the order in another order group
  • the distance between the addresses adjusts the attribution of the orders in the order group.
  • the adjusting module 41 is specifically configured to:
  • the any order is added to another order group to which the order corresponding to the second closest distance belongs.
  • the apparatus shown in FIG. 9 can perform the method of the embodiment shown in FIG. 4a.
  • the apparatus shown in FIG. 9 can perform the method of the embodiment shown in FIG. 4a.
  • the parts not described in detail in this embodiment reference may be made to the related description of the embodiment shown in FIG. 4a.
  • the implementation process and technical effects of the technical solution refer to the description in the embodiment shown in FIG. 4a, and details are not described herein again.
  • FIG. 10 is a schematic structural diagram of Embodiment 5 of an order processing apparatus according to an embodiment of the present disclosure. As shown in FIG. 10, on the basis of the embodiment shown in FIG. 6, the apparatus further includes: a path planning module 51.
  • the path planning module 51 is configured to use a shortest path algorithm to plan a delivery path of an order in the order group.
  • the apparatus shown in FIG. 10 can perform the method of the embodiment shown in FIG. 5.
  • the apparatus shown in FIG. 10 can perform the method of the embodiment shown in FIG. 5.
  • the parts not described in detail in this embodiment reference may be made to the related description of the embodiment shown in FIG.
  • the implementation process and technical effects of the technical solution refer to the description in the embodiment shown in FIG. 5, and details are not described herein again.
  • the structure of the order processing apparatus can be implemented as a server.
  • the processor 61 and the memory 62 can be included.
  • the memory 62 is configured to store a program supporting the order processing apparatus to execute the order processing method provided in any of the above embodiments, the processor 61 being configured to execute the program stored in the memory 62.
  • the program includes one or more computer instructions, wherein the one or more computer instructions are for execution by the processor 61.
  • the processor 61 is configured to: obtain an actual packet capacity according to a total number of multiple orders, where the multiple orders correspond to the same collection address; and select a current according to a distance between a delivery address of the plurality of orders and the collection address The clustering center order; based on the actual grouping capacity, clustering the un-clustered orders according to the distance between the un-clustering order of the plurality of orders and the delivery address of the cluster center order, An order group corresponding to the cluster center order is determined.
  • the processor 61 is further configured to perform all or part of the foregoing method steps.
  • the structure of the order processing device may further include a communication interface 63 for the order processing device to communicate with other devices or communication networks.
  • an embodiment of the present disclosure provides a computer storage medium for storing computer software instructions for use in an order processing apparatus, including a program for executing the order processing method in the above first aspect.
  • the device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, ie may be located A place, or it can be distributed to multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the embodiment. Those of ordinary skill in the art can understand and implement without deliberate labor.

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Abstract

Le mode de réalisation de la présente invention concerne un procédé de traitement de commande, un dispositif, un serveur et un support de stockage informatique. Le procédé consiste à : obtenir une capacité de groupement réelle selon un nombre total de commandes multiples ; sélectionner des commandes de centre de groupe actuel en fonction de distances entre des adresses de livraison respectives des multiples commandes et des adresses de distribution ; en fonction de la capacité de groupement réelle, en fonction de distances entre les adresses de livraison des commandes non groupées et des commandes de centre de groupe, regrouper les commandes non groupées pour déterminer un groupe de commandes correspondant aux commandes de centre de groupe. Comme les commandes de centre de groupe sont sélectionnées en fonction de la distance entre l'adresse de livraison et l'adresse de distribution, et les commandes groupées sont déterminées en fonction de la distance entre l'adresse de livraison de commande non groupée et l'adresse de livraison de commande de centre de groupe, des distances de livraison de différents groupes sont évidemment différentes et le niveau de regroupement des adresses de livraison des commandes dans le même groupe est relativement élevé, et la taille de groupe est conforme à la quantité de commandes, ce qui contribue à assurer que la taille du groupe de commandes qui est attribué à chaque livreur correspond à la capacité de livraison réelle et que la distance de livraison est relativement concentrée, ce qui améliore l'utilisation de la capacité de livraison.
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