Cargo delivery control method, device and computer readable storage medium

Abstract

The present disclosure relates to a warehouse-out control method and device of goods, and a computer readable storage medium, and relates to the technical fields of intelligent logistics and computers. The method of the present disclosure comprises: generating one or more path set orders according to a plurality of orders in an order pool; generating a picking set order according to the one or more path set orders; picking goods according to the picking set order; automatically distributing the picked goods to storage compartments according to each order corresponding to the picking set order and each path set order, wherein each order corresponds to one or more storage compartments; and sending a delivery task to one or more delivery personnel according to the one or more path set orders.

Description

Technical Field

[0001] This disclosure relates to the fields of smart logistics and computer technology, and in particular to a method, apparatus and computer-readable storage medium for controlling the outbound shipment of goods. Background Technology

[0002] With the development of internet and logistics technologies, people's lives have become increasingly convenient, allowing them to purchase goods without leaving home. Many supermarkets and stores offer delivery services, where users can place orders online, schedule delivery times, and wait for delivery personnel to arrive.

[0003] The in-store production model includes: picking goods according to user orders; after picking all orders within the same time period or wave, packing them together; and then having delivery personnel sort and bag the goods according to each user's order before delivery. Summary of the Invention

[0004] The inventors discovered that sorting errors occur when delivery personnel sort goods according to orders, relying entirely on the names of the goods for identification. This process is prone to errors and is very inefficient.

[0005] One of the technical problems this disclosure aims to solve is: how to improve the efficiency and accuracy of goods outbound and delivery.

[0006] According to some embodiments of this disclosure, a method for controlling the outbound shipment of goods is provided, comprising: generating one or more path set orders based on multiple orders in an order pool; generating picking set orders based on the one or more path set orders; picking goods based on the picking set orders; automatically allocating the picked goods to storage slots based on each order corresponding to the picking set orders and each path set order, wherein each order corresponds to one or more storage slots; and sending delivery tasks to one or more delivery personnel based on the one or more path set orders.

[0007] In some embodiments, generating a picking set order based on one or more path set orders includes: generating a picking set order based on one or more path set orders and one or more orders to be produced, provided that there are one or more orders to be produced in the order pool, wherein each order to be produced is an order whose latest production time is less than or equal to a threshold but has not been assigned to one or more path set orders.

[0008] In some embodiments, generating the picking collection order according to the one or more path collection orders and the one or more to-be-produced orders comprises: in a case where the total quantity of the one or more path collection orders and the one or more to-be-produced orders does not reach a preset production quantity, selecting one or more orders as pre-production orders according to the latest production time and the cargo category of the remaining orders in the order pool; and generating the picking collection order according to the one or more path collection orders, the one or more to-be-produced orders, and the one or more pre-production orders.

[0009] In some embodiments, automatically allocating the picked cargos into the storage compartments according to the respective orders corresponding to the picking collection order and the respective path collection orders comprises: automatically allocating the picked cargos into the storage compartments according to the respective orders corresponding to the picking collection order, the volume of the cargos in the respective orders, the respective path collection orders, and a storage compartment allocation strategy, wherein an order with a total volume of cargos less than or equal to the volume of a storage compartment corresponds to one storage compartment, and an order with a total volume of cargos greater than the volume of a storage compartment corresponds to multiple storage compartments.

[0010] In some embodiments, the storage compartment allocation strategy comprises: a first sub-strategy of allocating the cargos of the respective orders in the same path collection order into adjacent storage compartments, a second sub-strategy of allocating the cargos of the orders with delivery addresses located in the same preset area into the storage compartments corresponding to the preset area, and a priority of the first sub-strategy and the second sub-strategy.

[0011] In some embodiments, automatically allocating the picked cargos into the storage compartments according to the respective orders corresponding to the picking collection order, the volume of the cargos in the respective orders, the respective path collection orders, and a storage compartment allocation strategy comprises: for each picked cargo, determining the order to which the cargo belongs and whether the order to which the cargo belongs has been allocated a storage compartment; in a case where the order to which the cargo belongs has not been allocated a storage compartment and the priority of the first sub-strategy is higher than the priority of the second sub-strategy, determining whether there is an order with an allocated storage compartment in the path collection order to which the cargo belongs; and in a case where there is an order with an allocated storage compartment in the path collection order to which the cargo belongs, automatically storing the cargo into an idle storage compartment adjacent to the order with the allocated storage compartment.

[0012] In some embodiments, the method further comprises: identifying and screening out a preset category of the picked goods; and sending indication information to the allocation personnel, wherein the indication information comprises a storage compartment corresponding to the preset category of the goods, so that the allocation personnel stores the preset category of the goods in the corresponding storage compartment.

[0013] In some embodiments, the method further comprises: identifying and screening out a preset category of the picked goods; and sending indication information to the allocation personnel, wherein the indication information comprises a storage compartment corresponding to the preset category of the goods, so that the allocation personnel stores the preset category of the goods in the corresponding storage compartment.

[0014] In some embodiments, the method further comprises: identifying and screening out a preset category of the picked goods; and sending indication information to the allocation personnel, wherein the indication information comprises a storage compartment corresponding to the preset category of the goods, so that the allocation personnel stores the preset category of the goods in the corresponding storage compartment.

[0015] In some embodiments, the method further comprises: identifying and screening out a preset category of the picked goods; and sending indication information to the allocation personnel, wherein the indication information comprises a storage compartment corresponding to the preset category of the goods, so that the allocation personnel stores the preset category of the goods in the corresponding storage compartment.

[0016] In some embodiments, the preset constraint condition comprises at least one of: an earliest production time of the i th candidate collection order is greater than a sum of a current time and a preset parameter, wherein the earliest production time is an earliest time among production times of the orders in the i th candidate collection order; and a total number of the orders in the i th candidate collection order is less than a preset upper limit value; and in a case where the i th candidate collection order is divided into a preset type order set and a non-preset type order set, a delivery time of any preset type order in the preset type order set is greater than a delivery time of any non-preset type order in the non-preset type order set.

[0017] In some embodiments, generating the plurality of candidate set orders using all orders in the order pool comprises: processing all orders in the order pool using a first algorithm to generate the plurality of candidate set orders; wherein the first algorithm comprises: randomly selecting one order from the order pool; in the case of existing candidate set orders, if a matching position can be found in the existing candidate set orders using a preset strategy, inserting the randomly selected order into the matching position; if a matching position cannot be found in the existing candidate set orders, or there is no candidate set order at present, inserting the randomly selected order into a new candidate set order; repeating the random selection of one order from the order pool until there is no order in the order pool.

[0018] In some embodiments, generating the plurality of candidate set orders using all orders in the order pool comprises: processing all orders in the target set using a second algorithm to generate the plurality of candidate set orders; wherein the second algorithm comprises: dividing the orders of the order pool into seed orders and non-seed orders according to a preset rule; randomly selecting one seed order from the plurality of seed orders as a base order; selecting seed orders and non-seed orders that can be placed in the same set order as the base order using a preset strategy to generate a set order; repeating the random selection of one seed order from the plurality of seed orders as a base order until the plurality of seed orders are processed.

[0019] In some embodiments, generating the picking set order according to the one or more path set orders comprises: filtering all orders in a to-be-picked order pool using a preset rule to obtain a plurality of candidate orders, wherein the to-be-picked order pool includes orders included in the one or more path set orders; performing hierarchical clustering on the plurality of candidate orders to construct a clustering tree; performing hierarchical traversal on the clustering tree to select a target node that satisfies a preset condition from the clustering tree; and generating the picking set order using all candidate orders included in the target node.

[0020] In some embodiments, the hierarchical traversal of the clustering tree comprises: in the process of hierarchical traversal, if the root node of the clustering tree satisfies the preset condition, taking the root node of the clustering tree as the target node; if the root node of the clustering tree does not satisfy the preset condition, taking each child node of the root node of the clustering tree as a to-be-processed node respectively; judging whether the to-be-processed node satisfies the preset condition; if the to-be-processed node satisfies the preset condition, taking the to-be-processed node as the target node; if the to-be-processed node does not satisfy the preset condition, judging whether the to-be-processed node has child nodes; if the to-be-processed node has child nodes, taking each child node of the to-be-processed node as a current to-be-processed node respectively; and repeating the judgment of whether the current to-be-processed node satisfies the preset condition.

[0021] In some embodiments, the preset condition comprises at least one of the following conditions: a total number of articles corresponding to all candidate orders included in the to-be-processed node does not exceed a first threshold; a total number of candidate orders included in the to-be-processed node does not exceed a second threshold; and a current time is located in a time interval in which the pick-up group order is issued.

[0022] In some embodiments, the constructing the clustering tree by using the plurality of candidate orders comprises: generating a plurality of group orders corresponding to the plurality of candidate orders one by one, wherein each group order has a corresponding candidate order; placing the plurality of group orders into a clustering set; calculating a distance between each two group orders in the clustering set; merging two group orders with the smallest distance into a new group order, the new group order including all candidate orders included in the two group orders with the smallest distance; generating a node corresponding to the new group order; replacing the two group orders with the smallest distance with the new group order, so as to update the clustering set; repeating the calculation of the distance between each two group orders in the clustering set until there is only one group order in the clustering set; and constructing the clustering tree by using all generated nodes.

[0023] In some embodiments, the filtering all orders in the to-be-picked order pool by using the preset rule comprises: filtering all orders to obtain a plurality of to-be-processed orders for generating group orders from all orders; determining whether each to-be-processed order in the plurality of to-be-processed orders can be completed within a predetermined time; and if each to-be-processed order can be completed within the predetermined time, taking each to-be-processed order as a candidate order.

[0024] In some embodiments, the to-be-picked order pool further comprises at least one of one or more to-be-produced orders and one or more pre-produced orders, wherein each to-be-produced order is an order whose difference between the latest production time and the current time is less than or equal to a threshold but is not divided into one or more path group orders, and each pre-produced order is selected according to the latest production time and the cargo category of the remaining orders in the order pool.

[0025] According to some other embodiments of the present disclosure, a warehouse-out control device for goods is provided, comprising: a path group order module configured to generate one or more path group orders according to a plurality of orders in an order pool; a pick-up group order module configured to generate a pick-up group order according to the one or more path group orders; a picking module configured to pick up goods according to the pick-up group order; a distribution module configured to automatically distribute the picked-up goods into storage compartments according to respective orders corresponding to the pick-up group order and respective path group orders, wherein each order corresponds to one or more storage compartments; and an issuing module configured to send a delivery task to one or more delivery personnel according to the one or more path group orders.

[0026] According to still some embodiments of the present disclosure, provided is a warehouse-out control device for goods, comprising: a processor; and a memory coupled to the processor, configured to store instructions, which, when executed by the processor, cause the processor to perform the warehouse-out control method for goods according to any of the foregoing embodiments.

[0027] According to still some embodiments of the present disclosure, provided is a non-transitory computer-readable storage medium having stored thereon a computer program, wherein the program, when executed by a processor, implements the warehouse-out control method for goods according to any of the embodiments.

[0028] In the present disclosure, one or more path set orders are first generated, and a picking set order is generated according to the path set order, the goods are picked according to the picking set order, the picked goods are automatically subjected to secondary sorting, and are allocated to storage compartments, and then a delivery task is sent to a delivery personnel according to the one or more path set orders. According to each order corresponding to the picking set order and each path set order, the goods are automatically subjected to secondary sorting and are allocated to storage compartments, and the delivery personnel only needs to obtain the goods to be delivered from the corresponding compartments, without the need for manual secondary sorting, thereby improving the efficiency and accuracy of warehouse-out and delivery of the goods.

[0029] Other features and advantages of the present disclosure will become apparent from the following detailed description of exemplary embodiments thereof, with reference to the accompanying drawings. BRIEF DESCRIPTION OF DRAWINGS

[0030] In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure or the prior art, brief introductions will be given to the drawings needed in the embodiments or prior art description. Obviously, the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without any creative effort on the basis of these drawings.

[0031] Figure 1 A flowchart of a warehouse-out control method for goods according to some embodiments of the present disclosure is shown.

[0032] Figure 2 A flowchart of a warehouse-out control method for goods according to some other embodiments of the present disclosure is shown.

[0033] Figure 3A And Figure 3B A candidate set order according to some embodiments of the present disclosure is shown.

[0034] Figure 4A And Figure 4B A candidate set order according to some other embodiments of the present disclosure is shown.

[0035] Figure 5A schematic diagram of a collection order distance calculation according to an embodiment of the present disclosure;

[0036] Figure 6 A schematic diagram of a collection order distribution according to an embodiment of the present disclosure;

[0037] Figure 7 A schematic diagram of a cluster tree according to an embodiment of the present disclosure;

[0038] Figure 8 A schematic diagram of a cluster tree according to another embodiment of the present disclosure;

[0039] Figure 9 A schematic diagram of a structure of a warehouse-out control device for goods according to some embodiments of the present disclosure.

[0040] Figure 10 A schematic diagram of a structure of a warehouse-out control device for goods according to some other embodiments of the present disclosure.

[0041] Figure 11 A schematic diagram of a structure of a warehouse-out control device for goods according to some other embodiments of the present disclosure. DETAILED DESCRIPTION

[0042] The technical solutions in the embodiments of the present disclosure will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only some of the embodiments of the present disclosure, but not all the embodiments. The description of the at least one exemplary embodiment is actually only illustrative, but not as any limitation on the present disclosure and its application or use. Based on the embodiments in the present disclosure, all other embodiments obtained by those of ordinary skill in the art without creative work are within the scope of protection of the present disclosure.

[0043] The present disclosure provides a warehouse-out control method for goods, which will be described below with reference to the accompanying drawings. Figure 1

[0044] Figure 1 A flowchart of the warehouse-out control method for goods according to some embodiments of the present disclosure. As shown in the figure, the method of this embodiment includes steps S102-S110. Figure 1

[0045] In step S102, one or more path collection orders are generated according to a plurality of orders in an order pool.

[0046] After a user places an order, each order will enter the order pool and be further issued for generation. Each path collection order includes a plurality of orders, and a corresponding planning path is generated for each path collection order, which can enable the delivery personnel to complete the delivery of each order according to the planning path in one delivery. The generation process of the path collection order will be described in detail in subsequent embodiments. ​​

[0047] In step S104, the picking collection order is generated according to the one or more path collection orders.

[0048] In some embodiments, when there is one or more to-be-produced orders in the order pool, the picking collection order is generated according to the one or more path collection orders and the one or more to-be-produced orders, wherein each to-be-produced order is an order whose difference between the latest production time and the current time is less than or equal to a threshold value but is not divided into the one or more path collection orders.

[0049] There can be orders in the order pool that cannot be divided into path collection orders but have already reached the latest production time, and these orders are also used to generate the picking collection order as to-be-produced orders.

[0050] In some embodiments, when the total quantity of orders of the one or more path collection orders and the one or more to-be-produced orders does not reach a preset production quantity, one or more orders are selected as pre-production orders according to the latest production time and the type of goods of the remaining orders in the order pool; and the picking collection order is generated according to the one or more path collection orders, the one or more to-be-produced orders, and the one or more pre-production orders.

[0051] Since the delivery time selected by the user can be concentrated in certain time periods (peak periods, for example, 5-7 pm), and the order quantity of other time periods is small, in this case, the orders of the peak period can be pre-produced in the time period with small order quantity to improve the overall outbound efficiency. The total quantity of orders of the one or more path collection orders and the one or more to-be-produced orders obtained is taken as the order quantity of the current wave, and it is determined whether the order quantity of the current wave reaches a preset production quantity (capacity). If not, one or more orders can be selected from the remaining orders in the order pool as pre-production orders to join the current wave, so that the order quantity of the current wave reaches or approaches the preset production quantity.

[0052] The selected pre-production orders cannot contain goods of a preset type, for example, cannot contain special goods such as temperature-controlled and real-time processing goods. The latest production time of the pre-production order can be in the peak period or other time period configured in advance. The pre-production order can not be outbounded for delivery first, and is reminded to be outbounded at the latest picking time or combined with other orders to generate a collection order.

[0053] Subsequent embodiments will describe in detail the method for generating the picking collection order.

[0054] In step S106, the goods are picked according to the picking collection order.

[0055] The picking collection order can be sent to the corresponding picking personnel for picking, or automatically picked by the equipment.

[0056] In step S108, the picked goods are automatically allocated to the storage compartments according to the respective orders corresponding to the order collection order and the respective path collection orders.

[0057] In some embodiments, the picked goods are automatically allocated to the storage compartments according to the respective orders corresponding to the order collection order, the volume of the goods in the respective orders, the respective path collection orders, and the storage compartment allocation strategy, wherein an order whose total volume of goods is less than or equal to the volume of the storage compartment corresponds to one storage compartment, and an order whose total volume of goods is greater than the volume of the storage compartment corresponds to multiple storage compartments.

[0058] In some embodiments, the storage compartment allocation strategy includes a first sub-strategy of allocating the goods of the respective orders in the same path collection order to adjacent storage compartments (for example, the goods of the respective orders in the same path collection order are stored in the storage compartments in the same column), a second sub-strategy of allocating the goods of the orders whose delivery addresses are located in the same preset area to the storage compartments corresponding to the preset area, and the priority of the first sub-strategy and the second sub-strategy.

[0059] The first sub-strategy allows the respective orders in the same path collection order to be allocated to the storage compartments in a concentrated manner, which can enable the delivery personnel to quickly obtain the goods in the same path collection order, reduce the outbound time difference of the respective goods, and improve the outbound efficiency and the delivery efficiency of the goods. The second sub-strategy allows the orders in the same preset area to be allocated to the storage compartments in a concentrated manner. For the to-be-produced orders, pre-produced orders, and the like that do not belong to the path collection orders, the second sub-strategy can be used to allocate the storage compartments, and the probability that the orders in the same preset area are delivered by the same delivery personnel is high, so that allocating the storage compartments in a concentrated manner can improve the outbound efficiency and the delivery efficiency of the goods. The storage compartments corresponding to the respective preset areas can be pre-allocated and bound with the distribution rules of the orders, which facilitates the delivery personnel to obtain the goods.

[0060] The picked goods can be automatically allocated to the storage compartments by using a wall device. For example, the respective orders corresponding to the order collection order, the respective path collection orders, and the storage compartment allocation strategy are sent to the wall device, and the picked goods are placed in the wall device for automatic distribution (the goods in the same order are divided together) and storage.

[0061] In some embodiments, for each picked goods, the order to which the goods belong is determined, and whether the order to which the goods belong is assigned a storage compartment; in the case that the order to which the goods belong is not assigned a storage compartment and the first sub-strategy priority is higher than the second sub-strategy, it is determined whether there is an order assigned a storage compartment in the path set order to which the goods belong; in the case that there is an order assigned a storage compartment in the path set order to which the goods belong, the goods are automatically stored in the adjacent idle storage compartment of the order assigned a storage compartment.

[0062] In the case that the order to which the goods belong is not assigned a storage compartment and the order to which the goods belong does not belong to any path set order, the goods are stored in the corresponding storage compartment according to the delivery address of the order to which the goods belong.

[0063] Further, in the case that the order to which the goods belong is assigned a storage compartment, it is determined whether the volume of the goods is less than or equal to the remaining volume of the assigned storage compartment; in the case that the volume of the goods is less than or equal to the remaining volume of the assigned storage compartment, the goods are automatically stored in the assigned storage compartment; in the case that the volume of the goods is greater than the remaining volume of the assigned storage compartment, the goods are automatically stored in the adjacent idle storage compartment of the assigned storage compartment.

[0064] The distribution wall device can identify the order to which the goods belong by scanning the identification code of the goods, and then automatically distribute and store. After the goods of each order are stored in the corresponding storage compartment, the light can be prompted, and the corresponding small ticket can be printed.

[0065] In some embodiments, a preset category of goods in the picked goods is identified and screened; indication information is sent to the distribution personnel, wherein the indication information includes the storage compartment corresponding to the goods of the preset category, so that the distribution personnel store the goods of the preset category in the corresponding storage compartment.

[0066] The goods of the preset category, such as fragile goods, food, goods with excessive weight, etc., can be manually stored in the corresponding storage compartment, and the remaining picked goods are automatically distributed to the storage compartment.

[0067] In order to improve efficiency, a part of the picked goods can also be distributed to the distribution personnel for automatic distribution and storage. Both automatic distribution and manual distribution are supported, and the two modes support simultaneous distribution.

[0068] In step S110, one or more delivery tasks are sent to one or more delivery personnel according to one or more path set orders.

[0069] When the goods are delivered, the goods in the storage compartments corresponding to the same path set order on the distribution wall device can be taken out by box, and the empty box can be loaded into the storage compartment.

[0070] In view of the delivery time difference and the delivery time limit, it may not be possible to complete the collection according to the path set order, and real-time secondary calculation of the delivery or the order to be delivered is required, and the system is assigned to the delivery personnel for direct collection.

[0071] In some embodiments, for each path set order, if there is an uncompleted order in the path set order, the collection order is regenerated according to each order corresponding to the path set order and the picking collection order, and the collection order is sent to a delivery personnel for delivery; if there is no uncompleted order in the path set order, the path set order is sent to a delivery personnel for delivery.

[0072] The method of regenerating the collection order can refer to the method of generating the path set order in the subsequent embodiments. The to-be-produced order that does not belong to the path set order can be used to regenerate the collection order, or can be regenerated with other orders or path set orders before delivery. For the pre-produced order, the collection order can be regenerated with other orders or path set orders when delivery is required.

[0073] In the above embodiments, one or more path set orders are first generated, then the picking collection order is generated according to the path set order, the goods are picked according to the picking collection order, the goods that have been picked are automatically secondarily sorted, and are allocated to the storage compartment, and then the delivery task is sent to the delivery personnel according to one or more path set orders. According to each order corresponding to the picking collection order and each path set order, the goods are automatically secondarily sorted and allocated to the storage compartment, and the delivery personnel only needs to obtain the goods that need to be delivered from the corresponding compartment, without the need for manual secondary sorting, thereby improving the efficiency and accuracy of goods delivery and delivery.

[0074] The present disclosure provides a complete method of goods delivery from order processing to delivery task issuing. As shown in Figure 2 After the user places an order, the order enters the order pool, the orders in the order pool generate path set orders, and the path set orders, to-be-produced orders and pre-produced orders generate picking collection orders, the goods are picked according to the picking collection orders, the picked goods are automatically distributed according to the storage compartment distribution strategy, and after the distribution is completed, the real-time order is issued according to the path set order.

[0075] Some embodiments of generating path set orders are described below.

[0076] In some embodiments, a plurality of candidate set orders are generated by using all orders in the order pool at a preset period; in a case where an i-th candidate set order in the plurality of candidate set orders does not satisfy a preset constraint condition, all orders in the i-th candidate set order are moved to the order pool, 1≤i≤N, N being a total number of candidate set orders; and one or more candidate set orders satisfying the preset constraint condition are taken as one or more path set orders.

[0077] For example, the preset period is 1 minute.

[0078] In some embodiments, all orders in the order pool can be processed by using the following first algorithm or second algorithm to generate a plurality of candidate set orders.

[0079] The first algorithm can also be referred to as a greedy algorithm, and the specific content is as follows:

[0080] 1) Randomly select an order from the order pool.

[0081] 2) In a case where there is an existing candidate set order, if a matching position can be found in the existing candidate set order by using a preset strategy, the randomly selected order is inserted into the matching position.

[0082] For example, the preset strategy includes a condition that the delivery distance is the shortest when the same delivery personnel delivers in the same candidate set order. The set order generation problem can be converted into a VRP (Vehicle Routing Problem) for processing. The delivery path corresponding to the candidate set order can be planned according to the delivery address, the property of the goods, the expected time window, the single driving distance of the delivery personnel, and the like. The delivery path is used to deliver multiple orders with different time efficiencies at a single time by using the driving time of the delivery personnel, and to ensure that the goods are delivered on time according to the time window required by the user. The path set order can be continuously generated before order dispatching, and the path set order that is successfully set but not produced is dispatched for production.

[0083] For example, the order pool includes 3 orders, and the corresponding order numbers are {11, 24, 33}.

[0084] At present, there are two candidate set orders, which are: candidate set order one: 1-3-14-26, and candidate set order two: 5-2-7.

[0085] An order, i.e., order 11, is randomly extracted from the order pool, and then it is determined whether there is a position that satisfies the constraint condition of the VRP and increases the value of the objective function of the VRP the least in the candidate set order one and the candidate set order two. If such a position exists, the order 11 is inserted into the position.

[0086] It should be noted that, since the VRP is not the point of the present disclosure, it will not be described here.

[0087] 3) If a matching position cannot be found in the existing candidate set order, or there is no candidate set order at present, the randomly selected order is inserted into a new candidate set order.

[0088] For example, in the above embodiment, if it is determined in the set order one and the set order two that there is no position that meets the constraint condition of the VRP and that makes the value of the VRP target function increase the least, the order 11 is inserted into a new set order.

[0089] 4) Repeat the process of randomly selecting an order from the order pool until there is no order in the order pool.

[0090] The second algorithm can also be referred to as a seed order adsorption algorithm, and the details are as follows:

[0091] 1) According to a preset rule, the orders in the order pool are divided into seed orders and non-seed orders.

[0092] In some embodiments, the preset rule includes: in the order pool, the orders whose difference between the delivery time and the current time is less than a time difference threshold are taken as seed orders, and the orders in the order pool other than the seed orders are taken as non-seed orders.

[0093] That is, the orders that will soon reach the delivery time are taken as seed orders.

[0094] 2) Randomly select one seed order from the plurality of seed orders as a base order.

[0095] 3) Select the seed orders and non-seed orders that can be placed in the same set order as the base order according to a preset strategy to generate a set order.

[0096] In some embodiments, other orders are adsorbed in the strategy of the least increase in the VRP target function value on the basis of the base order to generate a set order.

[0097] 4) Repeat the process of randomly selecting one seed order from the plurality of seed orders as a base order until the plurality of seed orders are processed.

[0098] 5) After the plurality of seed orders are processed, if the order pool includes remaining orders, the first algorithm is used to process all the remaining orders in the order pool.

[0099] It should be noted that, in the optimization process, in addition to paying attention to whether the delivery distance of each delivery personnel is the shortest, the store's all-day set order rate also needs to be considered, and the set order rate directly affects the delivery efficiency of the delivery personnel. For example, the target function related to the set order rate is as follows:

[0100]

[0101] Where T represents the store's operating hours within a day; t represents the time point when the algorithm is invoked for processing. Let be the number of candidate orders generated by the algorithm in the t-th call. Let C be the number of orders for which no candidate set was formed during the t-th call of the algorithm. t For the t-th time, the orders that participate in the candidate set are obtained.

[0102] Candidate set orders can be generated based on the VRP objective function and the objective function related to the set order rate.

[0103] In some embodiments, after generating multiple candidate set orders using the first or second algorithm described above, a first optimization process is performed on the multiple candidate set orders to obtain an optimized candidate set order.

[0104] For example, the first optimization process includes: firstly, randomly selecting a predetermined number of candidate order sets as the first set of orders to be processed; next, moving at least one order from each of the first set of orders to be processed into an order pool; and then using the first algorithm described above to process all orders in the order pool. It should be noted that, to ensure the stability of the optimization process, if a candidate order set contains only two orders, then that candidate order set is selected.

[0105] In the first optimization process described above, an optimized set of candidate orders can be obtained by reorganizing the orders included in the candidate order set.

[0106] like Figure 3A As shown, there are currently 3 candidate order sets. Candidate order set 21 includes 5 orders, candidate order set 22 includes 2 orders, and order set 23 includes 3 orders. Figure 3B As shown, through the first optimization process described above, the orders included in candidate sets 21 and 22 were reorganized. In this case, candidate set 21 includes 4 orders, candidate set 22 includes 3 orders, and candidate set 23 remains unchanged.

[0107] In some embodiments, after the first optimization process, a second optimization process can be performed on the multiple candidate set orders to randomly optimize the candidate set orders and obtain further optimized candidate set orders.

[0108] For example, the second optimization processing includes: generating a random number at a preset frequency, if the random number is greater than a preset disturbance value, checking whether there is an independent seed order, wherein the independent seed order is a seed order which does not form a candidate set order with other orders. If there is an independent seed order, the independent seed order is moved into the order pool, and a predetermined number of candidate set orders meeting a preset condition are randomly selected as second to-be-processed set orders.

[0109] For example, the preset condition includes: the total number of orders in the second to-be-processed set order is less than a preset number threshold. That is, a set order with a smaller number of orders is selected as the second to-be-processed set order.

[0110] Next, all orders in each second to-be-processed set order are moved into the order pool. Finally, all orders in the order pool are processed by using a second algorithm.

[0111] As shown in Figure 4A , there are currently three candidate set orders. The candidate set order 31 includes five orders, the candidate set order 32 includes two orders, and the candidate set order 33 includes three orders. In addition, there is a seed order 30 which does not form a candidate set order with other orders. As shown in Figure 4B , through the second optimization processing, the seed order 30 forms a candidate set order 33 with one order originally included in the set order 31 and one order originally included in the candidate set order 32. Thus, the overall set rate is effectively improved.

[0112] It should be noted that, in Figure 4B , through the second optimization processing, one order originally in the candidate set order 32 does not form a set order with other orders. Since the order is a non-seed order, the order can be returned to the order pool to participate in the generation of the next set order, thereby increasing the probability of successful combination of the overall order.

[0113] After the method of the above embodiment, a plurality of candidate set orders are obtained, and one or more candidate set orders meeting a preset constraint condition are further screened as one or more path set orders.

[0114] In some embodiments, the preset constraint condition includes: an earliest production time of an i-th candidate set order is greater than a sum of a current time and a preset parameter, wherein the earliest production time is the earliest time among production times of orders in the i-th candidate set order; and a total number of orders in the i-th candidate set order is less than a preset upper limit value.

[0115] That is, the preset constraint condition is as follows:

[0116]

[0117] wherein pti represents the production time of order i, the s-th candidate set order in the candidate set order result obtained by the algorithm in the t-th time of calling, t represents the current calculation time.

[0118] In some embodiments, in the case that the i-th candidate set order is divided into a preset type order set and a non-pre-set type order set, the delivery time of any preset type order in the preset type order set is greater than the delivery time of any non-pre-set type order in the non-pre-set type order set. The preset type order set is, for example, a catering order.

[0119] That is, the corresponding preset constraint condition is as follows:

[0120]

[0121] wherein, is the delivery time of order i, is the delivery time of order j, Ctsp is the preset type order set obtained by the algorithm in the t-th time of calling, C tsc is the non-pre-set type order set obtained by the algorithm in the t-th time of calling.

[0122] In some embodiments, before moving all orders in the i-th candidate set order into the order pool, it is determined whether the difference between the latest delivery time of the i-th candidate set order and the current time is greater than a preset time threshold. In the case that the difference is greater than the preset time threshold, the moving of all orders in the i-th candidate set order into the order pool is performed.

[0123] That is, if the i-th candidate set order is not globally optimal, but the latest delivery time of the i-th candidate set order has not arrived, in this case, all orders in the i-th candidate set order are moved into the order pool so as to participate in the next set order optimization processing.

[0124] In some embodiments, in the case that the difference is not greater than the preset time threshold, the i-th candidate set order is processed for delivery.

[0125] That is, if the i-th candidate set order is not globally optimal, but the latest delivery time of the i-th candidate set order is about to arrive, in this case, the i-th candidate set order is processed for delivery so as to complete the processing of the i-th candidate set order on time.

[0126] In some embodiments, in the case that the i-th candidate set order satisfies the preset constraint condition, the i-th candidate set order is processed for delivery.

[0127] That is, if the ith candidate set order is globally optimal, the ith candidate set order does not need to be processed again, and the ith candidate set order is directly issued for processing.

[0128] In the set order optimization processing method provided by the above embodiments of the present disclosure, not only whether the delivery distance of each courier is the shortest is concerned, but also the set order rate of the store throughout the day is concerned, so that the generated set order is globally optimal.

[0129] Some embodiments of generating a picking set order are described below.

[0130] In some embodiments, all orders in the order pool to be picked are filtered using a preset rule to obtain a plurality of candidate orders, and the plurality of candidate orders are used for hierarchical clustering to construct a clustering tree; the clustering tree is hierarchically traversed to select a target node from the clustering tree that meets a preset condition; and all candidate orders included in the target node are used to generate a picking set order.

[0131] The order pool to be picked includes one or more orders included in one or more path set orders, and can also include at least one of one or more to-be-produced orders and one or more pre-produced orders.

[0132] In some embodiments, the filtering method is as follows.

[0133] 1) All orders in the order pool to be picked are filtered to obtain a plurality of to-be-processed orders for generating a picking set order from all orders.

[0134] For example, the all orders in the order pool to be picked can be filtered using a preset blacklist or whitelist.

[0135] 2) Determine whether an ith to-be-processed order in the plurality of to-be-processed orders can be completed within a predetermined time, 1≤i≤N, N being the total number of to-be-processed orders.

[0136] If the ith to-be-processed order can be completed within the predetermined time, step 3) is performed; otherwise, step 4) is performed.

[0137] For example, if the current time does not exceed the latest picking time of the ith order, it is determined that the ith to-be-processed order can be completed within the predetermined time, otherwise it is determined that the ith to-be-processed order cannot be completed within the predetermined time.

[0138] 3) The ith to-be-processed order is taken as a candidate order.

[0139] 4), the ith to-be-processed order is issued for processing.

[0140] That is, if the current time has exceeded the latest picking time of the ith order, the order is issued to reduce the delay time of the ith order as much as possible.

[0141] In some embodiments, the method of building a clustering tree is as follows.

[0142] 1) A plurality of set orders corresponding to a plurality of candidate orders are generated, wherein each set order has a corresponding candidate order.

[0143] For example, if there are 7 candidate orders F0-F6, 7 corresponding set orders p0-p6 are generated, wherein the candidate order F0 is included in the set order p0, the candidate order F1 is included in the set order p1, the candidate order F2 is included in the set order p2, and so on.

[0144] 2) The plurality of set orders are put into a clustering set.

[0145] 3) The distance between each two set orders in the clustering set is calculated.

[0146] In some embodiments, the distance between two set orders can be calculated by using centroid linkage.

[0147] Let the first set order be one of the two set orders, and the second set order be the other of the two set orders.

[0148] First, the first picking positions corresponding to all candidate orders in the first set order and the second picking positions corresponding to all candidate orders in the second set order are counted.

[0149] Next, the distance between each first picking position in the first picking positions and each second picking position in the second picking positions is calculated. For example, the distance here can be Euclidean distance.

[0150] Next, the distance between the first set order and the second set order is determined according to the average of all distances, the preset issuing time of all candidate orders in the first set order, and the preset issuing time of all candidate orders in the second set order.

[0151] For example, the distance D between the first set order and the second set order is:

[0152] D=D1+α(abs(T1-T2)) (4)

[0153] Where D1 is the average of all distances, T1 is the preset delivery time of all candidate orders in the first set of orders, T2 is the preset delivery time of all candidate orders in the second set of orders, abs is the absolute value function, and α is the weight value.

[0154] For example, such as Figure 5 As shown, the circle on the left represents the first batch order, which has two first picking locations. The circle on the right represents the second batch order, which has two second picking locations. The distance between each first picking location and each second picking location is calculated, and the average of the distances is calculated to obtain the parameter D1 mentioned above.

[0155] It should be noted that the second term on the right side of the equals sign in the above formula (4) serves to ensure that in the process of generating aggregated orders, not only the picking distance is considered, but also the expected delivery time of the orders is made as close as possible. Therefore, in cases of time urgency (expected delivery time is close to the current time), orders are tended to be aggregated together, thereby improving the efficiency of generating aggregated orders.

[0156] It should be noted that the preset delivery time for all candidate orders in the first batch of orders is the earliest of the latest picking times among all candidate orders in the first batch of orders. The preset delivery time for all candidate orders in the second batch of orders is the earliest of the latest picking times among all candidate orders in the second batch of orders.

[0157] 4) Merge the two sets of orders with the minimum distance into a new set of orders, which includes all candidate orders included in the two sets of orders with the minimum distance;

[0158] 5) Generate the node corresponding to the new set of orders.

[0159] 6) Replace the two set orders with the new set order in order to update the cluster set.

[0160] 7) Repeatedly calculate the distance between every two cluster orders in the cluster set until there is only one cluster order in the cluster set.

[0161] 8) Construct a clustering tree using all the generated nodes.

[0162] For example, a cluster set S has set orders p0-p6, that is:

[0163] S={p0, p1, p2, p3, p4, p5, p6}

[0164] The distribution of aggregate orders p0-p6 is as follows Figure 6 As shown.

[0165] In the set S, the distance between p5 and p6 is the smallest, so p5 and p6 are merged into a new set order p7, and the orders included in p7 are {F5, F6}. Next, the node relative to the set order p7 is generated, and the set S is updated. At this time, the set S is:

[0166] S = {p0, p1, p2, p3, p4, p7}

[0167] Next, since the distance between p4 and p7 is the smallest, p4 and p7 are merged into a new set order p8, and the orders included in p8 are {F4, F5, F6}. Next, the node relative to the set order p8 is generated, and the set S is updated. At this time, the set S is:

[0168] S = {p0, p1, p2, p3, p8}

[0169] Next, since the distance between p1 and p2 is the smallest, p1 and p2 are merged into a new set order p9, and the orders included in p9 are {F1, F2}. Next, the node relative to the set order p9 is generated, and the set S is updated. At this time, the set S is:

[0170] S = {p0, p9, p3, p8}

[0171] Next, since the distance between p0 and p9 is the smallest, p0 and p9 are merged into a new set order p10, and the orders included in p10 are {F0, F1, F2}. Next, the node relative to the set order p10 is generated, and the set S is updated. At this time, the set S is:

[0172] S = {p10, p3, p8}

[0173] Next, since the distance between p3 and p8 is the smallest, p3 and p8 are merged into a new set order p11, and the orders included in p11 are {F3, F4, F5, F6}. Next, the node relative to the set order p11 is generated, and the set S is updated. At this time, the set S is:

[0174] S = {p10, p11}

[0175] Next, since there are only set orders p10 and p11 in the set S, p10 and p11 are merged into a new set order p12, and the orders included in p12 are {F0, F1, F2, F3, F4, F5, F6}. Next, the node relative to the set order p12 is generated, and the set S is updated. At this time, the set S is:

[0176] S = {p12}

[0177] The cluster tree generated according to the generated nodes is as follows:Figure 7 as shown.

[0178] In some embodiments, the method of performing hierarchical traversal on the cluster tree is as follows.

[0179] In some embodiments, during the hierarchical traversal, if the root node of the cluster tree satisfies a preset condition, the root node of the cluster tree is taken as the target node.

[0180] In some embodiments, if the root node of the cluster tree does not satisfy the preset condition, each child node of the root node of the cluster tree is taken as a to-be-processed node respectively. Next, it is judged whether the to-be-processed node satisfies the preset condition. If the to-be-processed node satisfies the preset condition, the to-be-processed node is taken as the target node.

[0181] If the to-be-processed node does not satisfy the preset condition, it is judged whether the to-be-processed node has child nodes. If the to-be-processed node has child nodes, each child node of the to-be-processed node is taken as a current to-be-processed node respectively, and it is repeated to judge whether the current to-be-processed node satisfies the preset condition.

[0182] In some embodiments, the candidate orders in the plurality of candidate orders that are not included in the set order are moved into the order pool.

[0183] In some embodiments, the preset condition includes at least one of the following conditions:

[0184] 1) The total number of articles corresponding to all candidate orders included in the to-be-processed node does not exceed a first threshold;

[0185] 2) The total number of candidate orders included in the to-be-processed node does not exceed a second threshold;

[0186] 3) The current time is located in a set order issuing time interval.

[0187] For example, the set order issuing time interval is [preset issuing time-preset interval time, preset issuing time], wherein the preset issuing time is the earliest time among the latest picking times of the candidate orders included in the to-be-processed node.

[0188] Suppose the set order includes A order and B order. The latest picking time of A order is 13:40, the latest picking time of B order is 13:30, and the picking time of the set order is 5 minutes. Therefore, the latest picking time of the set order is 13:25. Assuming that the preset interval time is 1 minute, the issuing time interval of the set order is [13:24-13:25], and if the current time is within the interval, the set order is issued.

[0189] For example, the order picking time is (T + a * number of categories in the order + b * number of picking areas), where T is the picking preparation time, a is the time for the picker to switch categories, and b is the time for switching categories. These parameters can be configured according to the actual situation.

[0190] For example, suppose the SKUs (Stock Keeping Units) in a batch order are divided into 3 categories and distributed across 2 picking areas. The picking time is 30 seconds, the time for a picker to move from one category to another is 10 seconds, and the time to move from one picking area to another is 20 seconds. Then the picking time for this batch order is 30 seconds + 3 * 10 seconds + 20 * 2 seconds = 1 minute and 40 seconds.

[0191] In some embodiments, the method for generating a picking set order using all candidate orders included in the target node is as follows.

[0192] In some embodiments, such as Figure 7 As shown, if the root node D1 of the clustering tree meets the preset conditions, the root node of the clustering tree is taken as the target node, and then all candidate orders F0-F6 included in the root node D1 are generated into a set order.

[0193] That is, the set of orders C = {F0, F1, F2, F3, F4, F5, F6}.

[0194] In some embodiments, such as Figure 7 As shown, if the root node D1 of the clustering tree does not meet the preset conditions, and root node D1 has two child nodes D2 and D3, then child nodes D2 and D3 are checked respectively. If both child nodes D2 and D3 meet the preset conditions, then a set of orders C1 is generated based on all candidate orders F3-F6 included in child node D2, and a set of orders C2 is generated based on all candidate orders F0-F2 included in child node D3.

[0195] That is, the aggregate order C1 = {F3, F4, F5, F6}, and the aggregate order C2 = {F0, F1, F2}.

[0196] In some embodiments, such as Figure 8 As shown, the root node D1 of the clustering tree does not meet the preset conditions, and the root node D1 has two child nodes D2 and D3. Therefore, the child nodes D2 and D3 are detected respectively.

[0197] 1) If child node D2 does not meet the preset conditions, and child node D2 has child node D5, then child node D5 is checked. If child node D5 meets the preset conditions, then a set order C1 is generated based on all candidate orders F4-F6 included in child node D5.

[0198] 2) The child node D3 meets the preset condition, and the set order C2 is generated according to all the candidate orders F0-F2 included in the child node D3.

[0199] That is, the set order C1={F4, F5, F6}, and the set order C2={F0, F1, F2}.

[0200] In addition, the candidate order F3 not joined in the set order is moved into the order pool for the next set order generation process.

[0201] In some embodiments, as shown in FIG. 1, the root node D1 of the clustering tree does not meet the preset condition, and the root node D1 has two child nodes D2 and D3, and the child nodes D2 and D3 are detected respectively. Figure 8

[0202] 1) The child node D2 does not meet the preset condition, and the child node D2 has a child node D5, and the child node D5 is detected. If the child node D5 meets the preset condition, the set order C1 is generated according to all the candidate orders F4-F6 included in the child node D5.

[0203] 2) The child node D3 does not meet the preset condition, and the child node D3 has a child node D4, and the child node D4 is detected. If the child node D4 meets the preset condition, the set order C2 is generated according to all the candidate orders F1-F2 included in the child node D4.

[0204] That is, the set order C1={F4, F5, F6}, and the set order C2={F1, F2}.

[0205] In addition, the candidate orders F0 and F3 not joined in the set order are moved into the order pool for the next set order generation process.

[0206] In the set order generation method provided by the above embodiments of the present disclosure, hierarchical clustering is performed according to the distance between multiple orders to construct a clustering tree, and then hierarchical traversal is performed on the clustering tree to select a target node meeting the preset condition from the clustering tree, and then all the orders included in the target node are used to generate a set order. Since all the orders in the same set order are clustered close to each other, the walking distance of the picker is effectively reduced, and the work efficiency is improved.

[0207] The present disclosure also provides a warehouse-out control device for goods, which is described below in conjunction with Figure 9

[0208] Figure 9 is a structural diagram of some embodiments of the warehouse-out control device for goods of the present disclosure. As shown in FIG. 1, the warehouse-out control device for goods of the present disclosure includes a clustering module 10, a set order generation module 20, an order pool 30, a set order pool 40, a set order distribution module 50, and a picker 60. Figure 9 ​​As shown, the device 90 of the embodiment includes a path set single module 910, a picking set single module 920, a picking module 930, a distribution module 940, and a delivery module 950.

[0209] The path set single module 910 is configured to generate one or more path set orders according to a plurality of orders in an order pool.

[0210] The path set single module 910 is configured to perform the method of generating a path set order in the foregoing embodiments.

[0211] The picking set single module 920 is configured to generate a picking set order according to one or more path set orders.

[0212] In some embodiments, the picking set single module 920 is configured to generate a picking set order according to one or more path set orders and one or more to-be-produced orders in the case that there is one or more to-be-produced orders in the order pool, wherein each to-be-produced order is an order whose difference between the latest production time and the current time is less than or equal to a threshold value but is not divided into the one or more path set orders.

[0213] In some embodiments, the picking set single module 920 is configured to select one or more orders as pre-production orders according to the latest production time and the cargo category of the remaining orders in the order pool in the case that the total quantity of orders of the one or more path set orders and the one or more to-be-produced orders does not reach a preset production quantity; and generate a picking set order according to the one or more path set orders, the one or more to-be-produced orders, and the one or more pre-production orders.

[0214] The picking set single module 920 is configured to perform the method of generating a picking set order in the foregoing embodiments.

[0215] The picking module 930 is configured to pick cargos according to a picking set order.

[0216] The distribution module 940 is configured to automatically distribute the picked cargos to storage compartments corresponding to each order and each path set order of the picking set order, wherein each order corresponds to one or more storage compartments.

[0217] In some embodiments, the distribution module 940 is configured to automatically distribute the picked cargos to storage compartments according to each order corresponding to the picking set order, the volume of the cargos in each order, each path set order, and a storage compartment distribution strategy, wherein an order whose total volume of cargos is less than or equal to the volume of a storage compartment corresponds to one storage compartment, and an order whose total volume of cargos is greater than the volume of a storage compartment corresponds to multiple storage compartments.

[0218] In some embodiments, the storage bin allocation strategy comprises a first sub-strategy of allocating the goods of each order in the same path set order to adjacent storage bins, a second sub-strategy of allocating the goods of orders with delivery addresses in the same preset area to the storage bins corresponding to the preset area, and a priority of the first sub-strategy and the second sub-strategy.

[0219] In some embodiments, the distribution module 940 is configured to determine, for each picked good, an order to which the good belongs, and whether the order to which the good belongs has been allocated a storage bin; in a case where the order to which the good belongs has not been allocated a storage bin and the priority of the first sub-strategy is higher than that of the second sub-strategy, determine whether there is an order with an allocated storage bin in the path set order to which the good belongs; and in a case where there is an order with an allocated storage bin in the path set order to which the good belongs, automatically store the good in an adjacent idle storage bin of the order with the allocated storage bin.

[0220] In some embodiments, the distribution module 940 is configured to, in a case where the order to which the good belongs has been allocated a storage bin, determine whether the volume of the good is less than or equal to the remaining volume of the allocated storage bin; in a case where the volume of the good is less than or equal to the remaining volume of the allocated storage bin, automatically store the good in the allocated storage bin; and in a case where the volume of the good is greater than the remaining volume of the allocated storage bin, automatically store the good in an adjacent idle storage bin of the allocated storage bin.

[0221] In some embodiments, the distribution module 940 is further configured to identify and screen out goods of a preset category from the picked goods; and send indication information to the allocation personnel, wherein the indication information comprises the storage bin corresponding to the goods of the preset category, so that the allocation personnel stores the goods of the preset category in the corresponding storage bin.

[0222] In some embodiments, the distribution module 940 can be implemented by or arranged in a distribution wall device, or the distribution module 940 sends the picked goods, each order corresponding to the order-picking set order, the volume of the goods in each order, each path set order, and the storage bin allocation strategy to the distribution wall device, and uses the distribution wall device to automatically allocate the picked goods to the storage bins.

[0223] The delivery module 950 is configured to send a delivery task to one or more delivery personnel according to one or more path set orders.

[0224] In some embodiments, the delivery module 950 is configured to, for each route collection order, if there are incomplete orders in the route collection order, regenerate the collection order according to each order corresponding to the route collection order and the picking collection order, and send the collection order to a delivery person for delivery; if there are no incomplete orders in the route collection order, send the route collection order to a delivery person for delivery.

[0225] The goods outbound control device in the embodiments of this disclosure can be implemented by various computing devices or computer systems, as described below. Figure 10 as well as Figure 11 Describe it.

[0226] Figure 10 These are structural diagrams of some embodiments of the outbound control device for goods disclosed herein. For example... Figure 10 As shown, the apparatus 100 of this embodiment includes a memory 1010 and a processor 1020 coupled to the memory 1010. The processor 1020 is configured to execute the outbound control method for goods in any of the embodiments of this disclosure based on instructions stored in the memory 1010.

[0227] The memory 1010 may include, for example, system memory, fixed non-volatile storage media, etc. The system memory may store, for example, an operating system, application programs, a boot loader, a database, and other programs.

[0228] Figure 11 These are structural diagrams of other embodiments of the outbound control device for goods disclosed herein. For example... Figure 11 As shown, the device 110 of this embodiment includes a memory 1110 and a processor 1120, which are similar to the memory 1010 and processor 1020, respectively. It may also include an input / output interface 1130, a network interface 1140, a storage interface 1150, etc. These interfaces 1130, 1140, 1150, and the memory 1110 and processor 1120 can be connected, for example, via a bus 1160. The input / output interface 1130 provides a connection interface for input / output devices such as a display, mouse, keyboard, and touchscreen. The network interface 1140 provides a connection interface for various networked devices, such as connecting to a database server or cloud storage server. The storage interface 1150 provides a connection interface for external storage devices such as SD cards and USB flash drives.

[0229] Those skilled in the art will appreciate that embodiments of the disclosure can be supplied as a method, a system, or a computer program product. Thus, the disclosure can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the disclosure can take the form of a computer program product on one or more computer-usable non-transitory storage media (including but not limited to disk storage, CD-ROMs, optical storage devices, etc.) embodying computer readable program code thereon for use by or in connection with an instruction execution system. Program Code

[0230] The disclosure is described in reference to the flowchart and / or block diagrams of the method, apparatus (system) and computer program product according to embodiments of the disclosure. It should be understood that each flow and / or block in the flowchart and / or block diagrams, and a combination of flows and / or blocks in the flowchart and / or block diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, a special purpose computer, an embedded processor or other programmable data processing apparatus to produce a machine, so that the instructions, which are executed via the processor of the computer or other programmable data processing apparatus, generate a means for implementing the functions specified in the flowchart and / or block diagrams of the flowchart and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the function specified in the flow or flows and / or block or blocks.

[0231] These computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer readable memory produce a manufacture product including instruction means, which implement the functions specified in the flowchart and / or block diagrams of the flowchart and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the function specified in the flow or flows and / or block or blocks.

[0232] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operational steps are performed on the computer or other programmable data processing apparatus to generate a computer implemented process, so that the instructions executed on the computer or other programmable data processing apparatus provide a process for implementing the functions specified in the flowchart and / or block diagrams of the flowchart and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 Figure 1 means for carrying out the function specified in the flow or flows and / or block or blocks.

[0233] The above description is merely the preferred embodiment of the disclosure, and is not intended to limit the disclosure. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the disclosure shall be included in the protection scope of the disclosure.

Claims

1. A method for warehouse-out control of goods, comprising: generating one or more path set orders according to a plurality of orders in an order pool; generating a picking set order according to the one or more path set orders; picking goods according to the picking set order; automatically assigning the picked goods to storage compartments according to respective orders and respective path set orders corresponding to the picking set order, wherein each order corresponds to one or more storage compartments; sending delivery tasks to one or more delivery personnel according to the one or more path set orders; wherein the generating one or more path set orders according to a plurality of orders in an order pool comprises: generating a plurality of candidate set orders using all orders in the order pool at a preset period; in a case where an i th candidate set order in the plurality of candidate set orders does not satisfy a preset constraint condition, moving all orders in the i th candidate set order into the order pool, 1≤i≤N, N being a total number of candidate set orders; taking one or more candidate set orders satisfying the preset constraint condition as the one or more path set orders; wherein the preset constraint condition comprises at least one of: an earliest production time of the i th candidate set order being greater than a sum of a current time and a preset parameter, wherein the earliest production time is an earliest time among production times of orders in the i th candidate set order; and a total number of orders in the i th candidate set order being less than a preset upper limit value; in a case where the i th candidate set order is divided into a preset type order set and a non-pre-set type order set, a delivery time of any preset type order in the preset type order set being greater than a delivery time of any non-pre-set type order in the non-pre-set type order set.

2. The delivery control method according to claim 1, wherein the generating a picking set order according to the one or more path set orders comprises: in a case where one or more to-be-produced orders exist in the order pool, generating the picking set order according to the one or more path set orders and the one or more to-be-produced orders, wherein each to-be-produced order is an order whose difference between a latest production time and a current time is less than or equal to a threshold value but is not divided into the one or more path set orders.

3. The delivery control method according to claim 2, wherein the generating a picking set order according to the one or more path set orders and the one or more to-be-produced orders comprises: in a case where a total number of orders in the one or more path set orders and the one or more to-be-produced orders does not reach a preset production amount, selecting one or more orders as pre-production orders according to a latest production time and a goods category of remaining orders in the order pool; generating the picking set order according to the one or more path set orders, the one or more to-be-produced orders, and the one or more pre-production orders.

4. The delivery control method according to claim 1, wherein the automatically assigning the picked goods to storage compartments according to respective orders and respective path set orders corresponding to the picking set order comprises: According to the respective orders corresponding to the order collection order, the volume of the goods in the respective orders, the respective path collection orders, and a storage compartment allocation strategy, the picked goods are automatically allocated to the storage compartments, wherein an order whose total volume of goods is less than or equal to the volume of a storage compartment corresponds to one storage compartment, and an order whose total volume of goods is greater than the volume of a storage compartment corresponds to multiple storage compartments.

5. The delivery control method according to claim 4, wherein The storage compartment allocation strategy comprises a first sub-strategy of allocating the goods of the respective orders in the same path collection order to adjacent storage compartments, a second sub-strategy of allocating the goods of the orders whose delivery addresses are located in the same preset area to the storage compartments corresponding to the preset area, and a priority of the first sub-strategy and the second sub-strategy.

6. The delivery control method according to claim 5, wherein The automatic allocation of the picked goods to the storage compartments according to the respective orders corresponding to the order collection order, the volume of the goods in the respective orders, the respective path collection orders, and the storage compartment allocation strategy comprises: For each picked good, determining the order to which the good belongs, and whether the order to which the good belongs has been allocated a storage compartment; In the case that the order to which the good belongs has not been allocated a storage compartment and the priority of the first sub-strategy is higher than that of the second sub-strategy, determining whether there is an order to which a storage compartment has been allocated in the path collection order to which the good belongs; In the case that there is an order to which a storage compartment has been allocated in the path collection order to which the good belongs, automatically storing the good in an idle storage compartment adjacent to the order to which a storage compartment has been allocated.

7. The control method according to claim 6, wherein The automatic allocation of the picked goods to the storage compartments according to the respective orders corresponding to the order collection order, the volume of the goods in the respective orders, the respective path collection orders, and the storage compartment allocation strategy further comprises: In the case that the order to which the good belongs has been allocated a storage compartment, determining whether the volume of the good is less than or equal to the remaining volume of the allocated storage compartment; In the case that the volume of the good is less than or equal to the remaining volume of the allocated storage compartment, automatically storing the good in the allocated storage compartment; In the case that the volume of the good is greater than the remaining volume of the allocated storage compartment, automatically storing the good in an idle storage compartment adjacent to the allocated storage compartment.

8. The warehouse-out control method according to claim 1, further comprising: identifying and screening goods of a preset category from the picked goods; sending indication information to an allocation personnel, wherein the indication information comprises a storage compartment corresponding to the goods of the preset category, so that the allocation personnel stores the goods of the preset category in the corresponding storage compartment.

9. The delivery control method according to Claim 1, wherein The sending of the delivery task to one or more delivery personnel according to the one or more path collection orders comprises: for each path collection order, in the case that there is an uncompleted order in the path collection order, regenerating a collection order according to the respective orders corresponding to the order collection order and the path collection order, and sending the collection order to one delivery personnel for delivery; in the case that there is no uncompleted order in the path collection order, sending the path collection order to one delivery personnel for delivery.

10. The delivery control method according to Claim 1, wherein The generating a plurality of candidate collection orders by using all orders in the order pool comprises: processing all orders in the order pool by using a first algorithm to generate a plurality of candidate collection orders; wherein the first algorithm comprises: randomly selecting an order from the order pool; in the case of an existing candidate collection order, if a matching position can be found in the existing candidate collection order by using a preset strategy, inserting the randomly selected order into the matching position; if a matching position cannot be found in the existing candidate collection order, or there is no candidate collection order at present, inserting the randomly selected order into a new candidate collection order; repeating the step of randomly selecting an order from the order pool until there is no order in the order pool.

11. The method of claim 1, wherein, The generating a plurality of candidate collection orders by using all orders in the order pool comprises: processing all orders in the target collection by using a second algorithm to generate a plurality of candidate collection orders; wherein the second algorithm comprises: dividing orders in the order pool into seed orders and non-seed orders according to a preset rule; randomly selecting a seed order from the plurality of seed orders as a basic order; selecting seed orders and non-seed orders that can be placed in the same collection order as the basic order by using a preset strategy to generate a collection order; repeating the step of randomly selecting a seed order from the plurality of seed orders as a basic order until the plurality of seed orders are processed.

12. The delivery control method according to Claim 1, wherein The generating a picking collection order according to the one or more path collection orders comprises: filtering all orders in a to-be-picked order pool by using a preset rule to obtain a plurality of candidate orders, wherein the to-be-picked order pool includes orders included in the one or more path collection orders; performing hierarchical clustering on the plurality of candidate orders to construct a clustering tree; performing hierarchical traversal on the clustering tree to select a target node that satisfies a preset condition from the clustering tree; generating the picking collection order by using all candidate orders included in the target node.

13. The delivery control method according to claim 12, wherein The performing hierarchical traversal on the clustering tree comprises: in the process of hierarchical traversal, if a root node of the clustering tree satisfies the preset condition, taking the root node of the clustering tree as a target node; if the root node of the clustering tree does not satisfy the preset condition, taking each child node of the root node of the clustering tree as a to-be-processed node respectively; judging whether the to-be-processed node satisfies the preset condition; if the to-be-processed node satisfies the preset condition, taking the to-be-processed node as a target node; if the to-be-processed node does not satisfy the preset condition, judging whether the to-be-processed node has a child node; if the to-be-processed node has a child node, taking each child node of the to-be-processed node as a current to-be-processed node respectively; repeating the step of judging whether the current to-be-processed node satisfies the preset condition.

14. The delivery control method according to claim 13, wherein The preset condition comprises at least one of the following conditions: a total number of articles corresponding to all candidate orders included in the to-be-processed node does not exceed a first threshold; a total number of candidate orders included in the to-be-processed node does not exceed a second threshold; The current time is located in the dispatch time interval of the picking set order.

15. The delivery control method according to claim 12, wherein The constructing the clustering tree using the multiple candidate orders comprises: generating multiple set orders corresponding to the multiple candidate orders one by one, wherein each set order has a corresponding candidate order; putting the multiple set orders into a clustering set; calculating the distance between each two set orders in the clustering set; merging two set orders with the minimum distance into a new set order, wherein the new set order includes all candidate orders included in the two set orders with the minimum distance; generating a node corresponding to the new set order; updating the clustering set by replacing the two set orders with the minimum distance with the new set order; repeating the calculation of the distance between each two set orders in the clustering set until there is only one set order in the clustering set; constructing the clustering tree using all generated nodes.

16. The delivery control method according to claim 12, wherein The filtering all orders in the picking order pool using the preset rule comprises: filtering the all orders to obtain multiple to-be-processed orders for generating set orders from the all orders; judging whether each to-be-processed order in the multiple to-be-processed orders can be completed within a predetermined time; if the each to-be-processed order can be completed within the predetermined time, the each to-be-processed order is taken as the candidate order.

17. The delivery control method according to claim 12, wherein The picking order pool further comprises at least one of one or more to-be-produced orders and one or more pre-produced orders, wherein each to-be-produced order is an order whose difference between the latest production time and the current time is less than or equal to a threshold value but is not divided into the one or more path set orders, and each pre-produced order is selected according to the latest production time and the goods category of the remaining orders in the order pool.

18. A warehouse-out control device for goods, comprising: a path set order module configured to generate one or more path set orders according to multiple orders in an order pool, wherein a preset period is used to generate multiple candidate set orders using all orders in the order pool, all orders in an i-th candidate set order in the multiple candidate set orders are moved into the order pool in a case where the i-th candidate set order does not satisfy a preset constraint condition, 1≤i≤N, N being a total number of candidate set orders, one or more candidate set orders satisfying the preset constraint condition are taken as the one or more path set orders, the preset constraint condition comprising at least one of: an earliest production time of the i-th candidate set order being greater than a sum of a current time and a preset parameter, wherein the earliest production time is an earliest time among production times of orders in the i-th candidate set order; and a total number of orders in the i-th candidate set order being less than a preset upper limit value; in a case where the i-th candidate set order is divided into a preset type order set and a non-pre-set type order set, a delivery time of any preset type order in the preset type order set being greater than a delivery time of any non-pre-set type order in the non-pre-set type order set. a picking collection order module configured to generate a picking collection order according to the one or more path collection orders; a picking module configured to pick the goods according to the picking collection order; a distribution module configured to automatically distribute the picked goods into storage bins according to each order and each path collection order corresponding to the picking collection order, wherein each order corresponds to one or more storage bins; a sending module configured to send a delivery task to one or more delivery personnel according to the one or more path collection orders.

19. A warehouse-out control device for goods, comprising: a processor; and a memory coupled to the processor and configured to store instructions, which, when executed by the processor, cause the processor to perform the warehouse-out control method for goods according to any one of claims 1-17.

20. A non-transitory computer readable storage medium having stored thereon a computer program, wherein, The program, when executed by the processor, implements the steps of the method according to any one of claims 1-17.

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