CN110659760A - Configuration method and system for warehouse storage position - Google Patents

Configuration method and system for warehouse storage position Download PDF

Info

Publication number
CN110659760A
CN110659760A CN201810720612.6A CN201810720612A CN110659760A CN 110659760 A CN110659760 A CN 110659760A CN 201810720612 A CN201810720612 A CN 201810720612A CN 110659760 A CN110659760 A CN 110659760A
Authority
CN
China
Prior art keywords
sequence
sequences
arrangement
warehouse
category
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201810720612.6A
Other languages
Chinese (zh)
Other versions
CN110659760B (en
Inventor
吴朝恬
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Beijing Jingdong Zhenshi Information Technology Co Ltd
Original Assignee
Beijing Jingdong Zhenshi Information Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beijing Jingdong Zhenshi Information Technology Co Ltd filed Critical Beijing Jingdong Zhenshi Information Technology Co Ltd
Priority to CN201810720612.6A priority Critical patent/CN110659760B/en
Publication of CN110659760A publication Critical patent/CN110659760A/en
Application granted granted Critical
Publication of CN110659760B publication Critical patent/CN110659760B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR 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
    • G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders

Abstract

The utility model provides a configuration method and system for warehouse storage space, the method comprises obtaining order data, wherein the order data relates to a plurality of orders of a plurality of categories; acquiring storage position data of a warehouse and attribute information of each of multiple categories; determining a storage space required by each category according to the storage data of the warehouse and the attribute information of each category; sorting a plurality of categories related to order data to obtain a plurality of sequences with different sorting sequences; and configuring a corresponding storage position for each category according to the arrangement sequence of the first target sequence in the plurality of sequences and the storage position space required by each category. The present disclosure also provides a computer system and a readable storage medium.

Description

Configuration method and system for warehouse storage position
Technical Field
The present disclosure relates to the field of warehouse logistics, and more particularly, to a configuration method and system for warehouse bays, a computer system, and a computer-readable storage medium.
Background
Warehouses are becoming increasingly important for commercial operations as an important location for storing goods. To improve logistics efficiency, different items may often be placed in the same warehouse. When order data are taken, the goods need to enter a warehouse goods picking area, the goods are sequentially moved to shelves where goods are located for picking, and the goods leave the goods picking area after the goods are picked. However, the goods in the warehouse are various in types, thousands of goods and tens of thousands of goods are frequently selected, and the goods in the order are selected from a large number of goods, so that the goods picking task is heavy. The existing warehouse layout scheme comprises sorting goods according to the sales volume of the goods from large to small, and storing the goods in the order of picking the goods along the storage positions of the warehouse. Or clustering according to the goods and storing the goods according to the sales volume of the cluster category along the picking sequence of the storage positions of the warehouse.
In implementing the disclosed concept, the inventors found that there are at least the following problems in the related art: the warehouse layout scheme in the related art makes the picking path longer, resulting in low picking efficiency.
Disclosure of Invention
In view of the foregoing, the present disclosure provides a configuration method and system, a computer system, and a computer-readable storage medium for warehouse bays.
One aspect of the present disclosure provides a configuration method for warehouse bays, including acquiring order data, wherein the order data relates to a plurality of orders of a plurality of categories; acquiring storage position data of a warehouse and attribute information of each of the multiple categories; determining a storage space required by each type according to the storage data of the warehouse and the attribute information of each type; sorting the various categories related to the order data to obtain a plurality of sequences with different sorting sequences; and configuring a corresponding storage position for each category according to the arrangement sequence of the first target sequence in the plurality of sequences and the storage position space required by each category.
According to an embodiment of the present disclosure, configuring a corresponding bin for each category according to an arrangement order of a first target sequence in the plurality of sequences and a bin space required by each category includes: determining a picking distance of each order in the order data according to the arrangement sequence of the first target sequence and the storage space required by each category, wherein the picking distance is a path length through which goods in the order are picked according to a picking path, and the picking path is determined according to the storage space initially configured for each category; and determining whether to reconfigure the category corresponding to the storage position in the warehouse or not based on the picking distance of each order in the plurality of orders.
According to an embodiment of the present disclosure, determining whether to reconfigure the category corresponding to the storage position in the warehouse based on the picking distance of each of the plurality of orders includes: adding and calculating the picking distance of each order in the plurality of orders to obtain a calculation result; under the condition that the calculation result does not meet the preset condition, re-determining a second target sequence from the sequences with different arrangement orders; and reconfiguring the categories corresponding to the storage positions in the warehouse according to the re-determined arrangement sequence of the second target sequence and the storage position space required by each category.
According to an embodiment of the present disclosure, the method further includes: randomly determining two sequences from the plurality of sequences having different arrangement orders; determining whether a crossover operation is required to be performed on the arrangement order of the two sequences, wherein the crossover operation is used for exchanging the articles arranged at the corresponding positions of the two sequences so as to change the arrangement order of the two sequences; under the condition that the arrangement sequence of the two sequences needs to be crossed, exchanging the categories arranged at the corresponding positions of the two sequences to obtain two sequences with the arrangement sequence changed; and reconfiguring the categories corresponding to the storage positions in the warehouse according to the arrangement sequence of the two sequences after the arrangement sequence is changed and the storage position space required by each category.
According to an embodiment of the present disclosure, the method further includes: randomly determining a sequence from the plurality of sequences having different arrangement orders; determining whether a mutation operation is required to be performed on the arrangement order of the one sequence, wherein the mutation operation is used for exchanging the articles arranged at different positions of the one sequence so as to change the arrangement order of the one sequence; under the condition that the variation operation needs to be carried out on the arrangement sequence of the sequence, exchanging the varieties arranged at different positions of the sequence to obtain a sequence with the changed arrangement sequence; and reconfiguring the categories corresponding to the storage positions in the warehouse according to the arrangement sequence of the sequence after the arrangement sequence is changed and the storage position space required by each category.
According to an embodiment of the present disclosure, the method further includes: grouping the sequences with different arrangement sequences to obtain a plurality of groups of sequence sets, wherein each group of sequence sets comprises one or more sequences; respectively determining a third target sequence from each group of sequence sets in parallel to obtain a plurality of third target sequences; and configuring a corresponding storage position for each of the multiple categories in parallel according to the arrangement order of each of the third target sequences and the storage position space required by each category.
According to another aspect of the present disclosure, there is also provided a configuration system for a warehouse storage location, comprising: the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring order data, and the order data relates to a plurality of orders of various categories; the second acquisition module is used for acquiring the storage position data of the warehouse and the attribute information of each of the multiple categories; the first determining module is used for determining the storage space required by each category according to the storage position data of the warehouse and the attribute information of each category; the ordering module is used for ordering the various categories related to the order data to obtain a plurality of sequences with different ordering sequences; and a first configuration module, configured to configure a corresponding storage for each category according to an arrangement order of a first target sequence in the plurality of sequences and a storage space required by each category.
According to an embodiment of the present disclosure, the first configuration module includes: a first determining unit, configured to determine a picking distance of each order in the order data according to the arrangement order of the first target sequence and the space of the storage space required by each category, where the picking distance is a length of a path through which goods in the order are picked according to a picking path, and the picking path is determined according to the storage space initially configured for each category; and a second determining unit, configured to determine whether to reconfigure the category corresponding to the storage location in the warehouse based on the picking distance of each of the plurality of orders.
According to an embodiment of the present disclosure, the second determining unit includes: the calculation subunit is used for summing the picking distance of each order in the plurality of orders to obtain a calculation result; a determining subunit, configured to re-determine a second target sequence from the plurality of sequences with different arrangement orders when the calculation result does not satisfy a preset condition; and the configuration subunit is used for reconfiguring the categories corresponding to the storage positions in the warehouse according to the re-determined arrangement sequence of the second target sequence and the storage position space required by each category.
According to an embodiment of the present disclosure, the above system further includes: a second determining module, configured to randomly determine two sequences from the plurality of sequences with different permutation orders; a third determining module, configured to determine whether a crossover operation needs to be performed on the arrangement order of the two sequences, where the crossover operation is used to exchange the categories arranged at corresponding positions of the two sequences to change the arrangement order of the two sequences; the first exchange module is used for exchanging the categories arranged at the corresponding positions of the two sequences under the condition that the arrangement sequence of the two sequences needs to be crossed, so as to obtain the two sequences with the changed arrangement sequence; and a second configuration module, configured to reconfigure the categories corresponding to the storage locations in the warehouse according to the arrangement order of the two sequences after changing the arrangement order and the storage location space required by each category.
According to an embodiment of the present disclosure, the above system further includes: a fourth determining module, configured to randomly determine a sequence from the plurality of sequences with different permutation orders; a fifth determining module, configured to determine whether a variation operation needs to be performed on the sequence order of the sequence, where the variation operation is used to exchange the categories arranged at different positions of the sequence to change the sequence order of the sequence; the second exchange module is used for exchanging the categories arranged at different positions of the sequence under the condition that the variation operation needs to be carried out on the arrangement sequence of the sequence to obtain the sequence with the changed arrangement sequence; and a third configuration module, configured to reconfigure the categories corresponding to the storage locations in the warehouse according to the arrangement order of the sequence after changing the arrangement order and the storage location space required by each category.
According to an embodiment of the present disclosure, the above system further includes: the grouping module is used for grouping the sequences with different arrangement sequences to obtain a plurality of groups of sequence sets, wherein each group of sequence sets comprises one or more sequences; a sixth determining module, configured to determine a third target sequence from each group of sequence sets in parallel, to obtain multiple third target sequences; and a fourth configuration module, configured to configure a corresponding storage location for each of the multiple categories in parallel according to an arrangement order of each of the multiple third target sequences and a storage location space required by each category.
Another aspect of the disclosure provides a computer system comprising one or more processors; a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the configuration method for warehouse bays as described above.
Another aspect of the disclosure provides a computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to implement a configuration method for warehouse bays as described above.
Another aspect of the present disclosure provides a computer program comprising computer executable instructions for implementing a method of configuration for warehouse bays as described above when executed.
According to the embodiment of the disclosure, because the class layout problem corresponding to the storage positions of the warehouse is abstracted as the sorting problem, one sorting sequence is a solution of the class sequence corresponding to the storage positions of the warehouse, and the corresponding storage positions are configured for each class according to the arrangement sequence of the first target sequence in the sequences and the storage position space required by each class, rather than being sequentially stored along the picking sequence of the storage positions of the warehouse according to the sorting of the goods sales volume from large to small, the technical problem of low picking efficiency caused by longer picking path due to the fact that the warehouse layout scheme in the related technology is at least partially overcome, and the technical effects of reducing the picking distance and improving the picking work efficiency of the warehouse are achieved.
According to an embodiment of the present disclosure, the order picking path of the orders may be determined according to an order of arrangement of the first target sequence in the plurality of sequences, and whether to reconfigure the category corresponding to the stock level in the warehouse may be determined based on the picking distance of each order in the plurality of orders such that, after reconfiguring the category corresponding to the stock level in the warehouse, a sum of the reconfigured picking distances of each order in the plurality of orders is smaller than a sum of the picking distances of each order in the plurality of orders before reconfiguring the stock level in the warehouse, whereby the categories corresponding to the stock level in the warehouse may be continuously reconfigured until the sum of the reconfigured picking distances of each order in the plurality of orders reaches a preset condition, for example, until the sum of the reconfigured picking distances of each order in the plurality of orders reaches a minimum or is smaller than or equal to a threshold value, and the like. Therefore, the technical problems that the picking path is long and the picking efficiency is low due to the fact that the warehouse layout scheme in the related technology is partially overcome, the picking distance is reduced, the warehouse picking work efficiency is improved, meanwhile, the requirements of upstream and downstream of a supply chain can be met, the logistics transportation efficiency is improved, and the technical effect of reasonable layout of storage positions of the warehouse is achieved.
Drawings
The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments of the present disclosure with reference to the accompanying drawings, in which:
FIG. 1 schematically illustrates an exemplary system architecture to which the configuration method and system for warehouse bays according to an embodiment of the present disclosure may be applied;
FIG. 2 schematically illustrates a flow chart of a configuration method for warehouse bays according to an embodiment of the present disclosure;
FIG. 3 schematically illustrates a schematic diagram of a warehouse storage according to an embodiment of the present disclosure;
FIG. 4 is a flow chart schematically illustrating configuring a corresponding bin for each item according to an arrangement order of a first target sequence in a plurality of sequences and a bin space required by each item according to an embodiment of the present disclosure;
FIG. 5 schematically illustrates a flow chart for determining whether to reconfigure a class corresponding to a bin in a warehouse based on a picking distance for each of a plurality of orders, in accordance with an embodiment of the present disclosure;
FIG. 6 schematically illustrates a flow chart of a configuration method for warehouse bays according to another embodiment of the present disclosure;
FIG. 7 schematically illustrates a schematic diagram of interleaving the permutation order of two sequences according to an embodiment of the disclosure;
FIG. 8 schematically illustrates a flow chart of a configuration method for warehouse bays according to another embodiment of the present disclosure;
FIG. 9 is a schematic diagram that schematically illustrates a mutation operation on an order of arrangement of a sequence, in accordance with an embodiment of the present disclosure;
FIG. 10 schematically illustrates a flow chart of a configuration method for warehouse bays according to another embodiment of the present disclosure;
FIG. 11 schematically illustrates a flow diagram for parallelizing processing of multiple sub-populations according to an embodiment of the present disclosure;
FIG. 12 schematically illustrates a block diagram of a configuration system for warehouse bays, in accordance with an embodiment of the present disclosure;
FIG. 13 schematically illustrates a block diagram of a first configuration module, in accordance with an embodiment of the present disclosure;
fig. 14 schematically shows a block diagram of a second determination unit according to an embodiment of the present disclosure;
FIG. 15 schematically illustrates a block diagram of a configuration system for warehouse bays, according to another embodiment of the present disclosure;
FIG. 16 schematically illustrates a block diagram of a configuration system for warehouse bays, according to another embodiment of the present disclosure;
FIG. 17 schematically illustrates a block diagram of a configuration system for warehouse bays, according to another embodiment of the present disclosure; and
FIG. 18 schematically illustrates a block diagram of a computer system suitable for implementing the above-described method, in accordance with an embodiment of the present disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.
Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). Where a convention analogous to "A, B or at least one of C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B or C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.). It will be further understood by those within the art that virtually any disjunctive word and/or phrase presenting two or more alternative terms, whether in the description, claims, or drawings, should be understood to contemplate the possibilities of including one of the terms, either of the terms, or both terms. For example, the phrase "a or B" should be understood to include the possibility of "a" or "B", or "a and B".
The embodiment of the disclosure provides a configuration method and a configuration system for warehouse storage positions, wherein the method comprises the steps of obtaining order data, wherein the order data relates to a plurality of orders of a plurality of categories; acquiring storage position data of a warehouse and attribute information of each of the multiple categories; determining a storage space required by each category according to the storage data of the warehouse and the attribute information of each category; sorting the multiple categories related to the order data to obtain multiple sequences with different sorting sequences; and configuring a corresponding storage position for each category according to the arrangement sequence of the first target sequence in the plurality of sequences and the storage position space required by each category.
Fig. 1 schematically illustrates an exemplary system architecture to which the configuration method and system for warehouse bays according to an embodiment of the present disclosure may be applied. It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios.
As shown in fig. 1, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired and/or wireless communication links, and so forth.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have installed thereon various communication client applications, such as a shopping-like application, a web browser application, a search-like application, an instant messaging tool, a mailbox client, and/or social platform software, etc. (by way of example only).
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (for example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that the configuration method for warehouse bays provided by the embodiments of the present disclosure may be generally performed by the server 105. Accordingly, the configuration system for warehouse bays provided by embodiments of the present disclosure may generally be located in server 105. The configuration method for warehouse bays provided by the embodiments of the present disclosure may also be performed by a server or a cluster of servers different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the configuration system for warehouse bays provided by the embodiments of the present disclosure may also be disposed in a server or server cluster that is different from the server 105 and is capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Alternatively, the configuration method for the warehouse storage provided by the embodiment of the present disclosure may also be executed by the terminal device 101, 102, or 103, or may also be executed by another terminal device different from the terminal device 101, 102, or 103. Accordingly, the configuration system for warehouse storage provided by the embodiment of the present disclosure may also be disposed in the terminal device 101, 102, or 103, or in another terminal device different from the terminal device 101, 102, or 103.
For example, the order data may be originally stored in any one of the terminal apparatuses 101, 102, or 103 (for example, but not limited to, the terminal apparatus 101), or may be stored on an external storage apparatus and may be imported into the terminal apparatus 101. Then, the terminal device 101 may locally perform the configuration method for the warehouse storage provided by the embodiment of the present disclosure, or send order data to other terminal devices, servers, or server clusters, and perform the configuration method for the warehouse storage provided by the embodiment of the present disclosure by the other terminal devices, servers, or server clusters receiving the order data.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Fig. 2 schematically illustrates a flow chart of a configuration method for warehouse bays according to an embodiment of the present disclosure.
As shown in fig. 2, the method includes operations S201 to S205.
In operation S201, order data is obtained, wherein the order data relates to a plurality of orders of a plurality of categories.
According to the embodiment of the disclosure, order data within a period of time, for example, order data of other periods of time such as a month or a half year, may be acquired. After the order data is obtained, the categories of the various products in each order may also be determined. Specifically, taking 2 orders as an example, the order 1 includes 10 items of goods of type a; order number 2 includes 5 items of type B and 5 items of type C, and thus the order data relates to 2 orders of the three categories A, B and C.
In operation S202, bin data of a warehouse and attribute information of each of a plurality of categories are acquired.
According to an embodiment of the present disclosure, the bin data of the warehouse may be position information and a volume of each bin, and the attribute information of each item may be volume, quantity, stock quantity, and the like of the item.
In operation S203, a bin space required for each of the categories is determined according to the bin data of the warehouse and the attribute information of each of the categories.
According to embodiments of the present disclosure, the required bin space for each category may be the number of bins, and there may be one or more bins for each category.
In operation S204, the multiple categories related to the order data are sorted to obtain multiple sequences with different sorting orders.
According to an embodiment of the present disclosure, for example, the order data relates to A, B and C three categories, and the sorting of A, B and C three categories may be A, B and C, A, C and B, B, A and C, B, C and A, C, A and B, C, B and A6 sequences, the 6 sequences having different ordering.
In operation S205, a corresponding bin is configured for each item according to the arrangement order of the first target sequence in the plurality of sequences and the required bin space for each item.
According to the embodiment of the disclosure, the storage positions of multiple article configurations can be sequentially determined according to the arrangement sequence of the first target sequence. Taking the first target sequence arrangement order of A, B and C as an example, item A may be placed in the storage location of shelf 1, item B may be placed in the storage location of shelf 2, and item C may be placed in the storage location of shelf 3. When A, B and C products are fewer in number and can be placed on the same shelf, they can be placed on the same shelf in the order of A, B and C.
According to the embodiment of the disclosure, after the storage positions of multiple types of goods are determined according to the arrangement sequence of each sequence, the arrangement sequence with the shortest picking distance is determined.
According to the embodiment of the disclosure, each sequence has a different arrangement sequence, and the storage positions of multiple categories are configured according to the arrangement sequence, so that the picking paths are not the same, different picking distances are obtained, and the categories corresponding to the storage positions of the warehouse can be reconfigured.
According to the embodiment of the disclosure, the warehouse comprises a plurality of storage positions, each storage position has corresponding position information, and the corresponding storage position is configured for each category, so that the categories corresponding to the storage positions are different, and therefore, the picking paths are also different.
According to an embodiment of the present disclosure, for example, fig. 3 schematically illustrates a schematic view of a warehouse storage according to an embodiment of the present disclosure.
As shown in fig. 3, the warehouse includes 3 shelves, shelf 1, shelf 2 and shelf 3, each shelf has a plurality of storage positions for placing different products, and the storage positions can also be used for placing containers for holding products of the same type. In the actual operation process, after taking orders, the orders need to enter a warehouse goods picking area, and walk to shelves where goods are located one by one to pick the goods, and leave the goods picking area after the goods picking is finished. The goods in the warehouse are various in types, and the goods corresponding to different storage positions are different in types, so that the goods picking paths are different.
According to the embodiment of the disclosure, after the order data is acquired, a corresponding storage position is configured for each of the multiple categories related to the order data. For example, 100 bins 1-100 on shelf 1 closest to the warehouse doorway may be assigned to category a, 50 bins 1-50 on shelf 2 to category B, and 200 bins 1-200 on shelf 3 to category C.
According to the embodiment of the disclosure, the configuration of the corresponding storage position for each of the multiple types of products related to the order data can also refer to warehouse storage position data, picking path data, maximum stock quantity data and product volume data of each product picking area, and the like.
The method shown in fig. 2 is further described with reference to fig. 4-11 in conjunction with specific embodiments.
Fig. 4 schematically shows a flowchart for configuring a corresponding bin for each category according to an arrangement order of a first target sequence in a plurality of sequences and a required bin space for each category according to an embodiment of the present disclosure.
As shown in fig. 4, configuring a corresponding bin for each category according to the arrangement order of the first target sequence in the plurality of sequences and the bin space required for each category includes operations S206 to S207.
In operation S206, a picking distance of each order in the order data is determined according to the arrangement order of the first target sequence and a required stock space for each category, wherein the picking distance is a length of a path through which items in the order are picked according to a picking path, and the picking path is determined according to an initially configured stock space for each category.
In operation S207, it is determined whether to reconfigure a class corresponding to a bin in the warehouse based on the picking distance of each of the plurality of orders.
According to the embodiment of the disclosure, after the corresponding storage space is initially configured for each category, for example, after the corresponding storage space is initially configured for each category according to the arrangement order of the first target sequence, the picking path of each category may be determined, and the picking path of each order may also be determined, and the picking distance of each order is calculated. According to an embodiment of the present disclosure, the pick distance may be a path length through which all items in the order are picked according to the pick path.
According to an embodiment of the present disclosure, the category corresponding to the storage position in the warehouse may be reconfigured based on the picking distance of each of the plurality of orders, such that after the category corresponding to the storage position in the warehouse is reconfigured, the sum of the picking distances re-determined for each of the plurality of orders is smaller than the sum of the picking distances for each of the plurality of orders before the storage position in the warehouse is reconfigured.
According to the embodiment of the disclosure, in order to reasonably arrange the storage positions of the warehouse and improve the picking efficiency, the categories corresponding to the storage positions in the warehouse can be reconfigured according to the picking distance of each order. For example, the order data includes order number 1 and order number 2, wherein the pick distance for order number 1 is 50.5 meters, the pick distance for order number 2 is 250.5 meters, and the total pick distance for both orders is 301 meters.
If the sum of the picking distances does not reach the minimum or is less than or equal to the threshold value, or the sum of the picking distances re-determined for each of the plurality of orders is less than the sum of the picking distances for each of the plurality of orders before the storage position in the warehouse is reconfigured, the item class corresponding to the storage position in the warehouse is required to be reconfigured based on the picking distances for each of the plurality of orders. For example, the total picking distance of the two orders is 301 meters, which is not the minimum distance or is less than or equal to the threshold, and other conditions, therefore, the categories corresponding to the storage positions in the warehouse are reconfigured, so that the total picking distance of the two orders is less than 301 meters after the categories corresponding to the storage positions in the warehouse are reconfigured.
Because the types corresponding to the storage positions in the warehouse are reconfigured, the storage positions of different types are changed, and the picking distance of the order is also changed at the moment.
According to the embodiment of the present disclosure, since the categories corresponding to the storage positions in the warehouse are reconfigured based on the picking distances of each of the plurality of orders, so that after the categories corresponding to the storage positions in the warehouse are reconfigured, the sum of the picking distances determined anew for each of the plurality of orders is smaller than the sum of the picking distances of each of the plurality of orders before the storage positions in the warehouse are reconfigured, the categories corresponding to the storage positions in the warehouse may be continuously reconfigured until the sum of the picking distances determined anew for each of the plurality of orders reaches the preset condition, for example, until the sum of the picking distances determined anew for each of the plurality of orders reaches the minimum or is smaller than or equal to the threshold value, and the like. Therefore, the technical problems that the picking path is long and the picking efficiency is low due to the fact that the warehouse layout scheme in the related technology is partially overcome, the picking distance is reduced, the warehouse picking work efficiency is improved, meanwhile, the requirements of upstream and downstream of a supply chain can be met, the logistics transportation efficiency is improved, and the technical effect of reasonable layout of storage positions of the warehouse is achieved.
Fig. 5 schematically illustrates a flow chart for determining whether to reconfigure a class corresponding to a bin in a warehouse based on a picking distance for each of a plurality of orders according to an embodiment of the present disclosure.
As shown in fig. 5, determining whether to reconfigure the categories corresponding to the bins in the warehouse based on the picking distance of each of the plurality of orders includes operations S208-S210.
In operation S208, the picking distance of each order in the plurality of orders is summed up to obtain a calculation result.
In operation S209, in the case where the calculation result does not satisfy the preset condition, the second target sequence is re-determined from the plurality of sequences having different arrangement orders.
In operation S210, the categories corresponding to the bays in the warehouse are reconfigured according to the re-determined arrangement order of the second target sequence and the bay space required for each category.
According to an embodiment of the present disclosure, the preset condition may be that the sum of the plurality of picking distances does not reach a minimum or is less than or equal to a threshold value, etc., or that the sum of the picking distances redetermined for each of the plurality of orders is less than the sum of the picking distances for each of the plurality of orders before reconfiguring the storage location in the warehouse.
According to the embodiment of the disclosure, if the sum of the picking distances of each order does not satisfy the preset condition after the last time of configuring the storage positions for the categories, the categories corresponding to the storage positions in the warehouse can be reconfigured again by determining one or more sequences from a plurality of sequences with different arrangement orders.
According to an embodiment of the present disclosure, the method for re-determining the second target sequence from a plurality of sequences having different permutation orders includes a plurality of methods, for example, one or more sequences may be randomly determined. Genetic algorithms may also be used, for example, for each individual in the population, the individual representing a sequence having a different rank order, and the sum of the pick distances sum for their corresponding historical ordersiLet the probability that this individual is selected be
Figure BDA0001717692970000141
Continuously selecting new generation individuals according to the probability until n is generatedpopAnd (4) forming a new generation of population by using new individuals. And acquiring one of the individuals from the new generation of population for reconfiguring the class corresponding to the storage position in the warehouse.
According to embodiments of the present disclosure, n may also be generated prior to composing a new generation populationpopA 1 to nthird) Randomly scrambling each sequence, wherein each sequence is used as an individual of a genetic algorithm population, all individuals form a population, and the position of each gene in the population represents a class in the warehouse layoutRelative order along the order of picking, where npopIs the size of the population, nthirdIndicates the number of genes, corresponding to the number of classes.
According to an embodiment of the present disclosure, if a gene in an individual comprises (1 to n)third) All values in (A) are feasible solutions. If there is a deletion or a duplication, it is not feasible. The non-feasible solution may be corrected, for example, by ranking the genes in the individual in an order of 53312, where 3 is a repeated gene, and correcting the individual may be by first traversing each gene to be corrected to find a Set of values that do not appear in the individual 53312uE.g. 4 does not occur, then Set is SetuTo 4, find the position of the repeated value 3 in the gene, SetuRandomly filling in these locations replaces one of the repeated values 3 to get a feasible solution, e.g., get the individual 54312, i.e., a feasible solution. According to the embodiment of the disclosure, if an infeasible solution occurs during the crossover operation, the correction can be performed by adopting the above correction method.
Fig. 6 schematically illustrates a flow chart of a configuration method for warehouse bays according to another embodiment of the present disclosure.
As shown in fig. 6, the method includes operations S211 to S214.
In operation S211, two sequences are randomly determined from a plurality of sequences having different arrangement orders.
In operation S212, it is determined whether a crossover operation is required for the arrangement order of the two sequences, wherein the crossover operation is used to exchange the articles arranged at the corresponding positions of the two sequences to change the arrangement order of the two sequences.
According to embodiments of the present disclosure, the plurality of sequences having different permutation orders may be as many as the plurality of individuals in the population in the genetic algorithm. And randomly selecting two individuals from the population in sequence by adopting a genetic algorithm, determining whether to carry out cross operation or not according to a certain probability (cross rate), randomly selecting two positions in the cross operation process, respectively extracting gene segments between the two positions from the two individuals, and then exchanging the gene segments of the two individuals. The crossing rate is a hyper-parameter, the setting of the values is generally selected and adjusted by a cross validation method, and the algorithm is easy to jump out of a local optimal solution due to the larger crossing rate, so that the algorithm is prevented from being over-fitted. But the algorithm is difficult to converge and a stable solution cannot be obtained. Therefore, the settings of the hyper-parameters need to be obtained comprehensively according to specific data and calculation limits, cross validation and other methods.
In operation S213, in the case that the sequence of the two sequences needs to be crossed, the categories arranged at the corresponding positions of the two sequences are exchanged to obtain the two sequences with the changed sequence.
Specifically, for example, fig. 7 schematically shows a schematic diagram of an operation of interleaving the arrangement order of two sequences according to an embodiment of the present disclosure.
As shown in fig. 7, the first sequences are arranged in the order of 1, 2, 3, 4 and 5, and the second sequences are arranged in the order of 5, 3, 2, 4 and 1. And exchanging 2 and 3 at corresponding positions of the first sequence with 3 and 2 at corresponding positions of the second sequence to obtain the two sequences with changed arrangement sequences. The arrangement order of the first sequence becomes 1, 3, 2, 4 and 5, and the arrangement order of the second sequence becomes 5, 2, 3, 4 and 1. In which the numbers 1, 2, 3, 4 and 5 characterize different classes. If the new two individuals after the crossover include repeated values, the sequence after the crossover also needs to be corrected.
In operation S214, the categories corresponding to the slots in the warehouse are reconfigured according to the arrangement order of the two sequences after the arrangement order is changed and the slot space required by each category.
According to the embodiment of the disclosure, the categories corresponding to the storage positions in the warehouse can be reconfigured according to the arrangement sequence of the two sequences after the arrangement sequence is changed and the storage position space required by each category, so that the picking path is determined according to the categories corresponding to the storage positions in the reconfigured warehouse, and the current picking distance of the order is calculated.
According to the embodiment of the disclosure, by performing the cross operation on the arrangement sequences of the two sequences, the sequences of different arrangement sequences can be continuously generated, that is, the arrangement sequence of the article types can be changed, so that the article types of the storage positions are reconfigured, and the technical effect of reasonably arranging the storage positions of the warehouse is achieved.
Fig. 8 schematically illustrates a flow chart of a configuration method for warehouse bays according to another embodiment of the present disclosure.
As shown in fig. 8, the method includes operations S215 to S218.
In operation S215, a sequence is randomly determined from a plurality of sequences having different arrangement orders.
In operation S216, it is determined whether a mutation operation is required on the arrangement order of a sequence, wherein the mutation operation is used to exchange the articles arranged at different positions of a sequence to change the arrangement order of a sequence.
According to embodiments of the present disclosure, the plurality of sequences having different permutation orders may be as many as the plurality of individuals in the population in the genetic algorithm. Selecting one individual from the population in sequence by adopting a genetic algorithm, determining whether to carry out mutation operation or not according to a certain probability (mutation rate), and randomly selecting two positions from genes of the individual to be mutated in the mutation operation process to exchange the genes on the two positions.
In operation S217, in the case where a mutation operation is required for the sequence of one sequence, the classes arranged at different positions of one sequence are exchanged to obtain one sequence with the changed sequence.
Specifically, for example, fig. 9 schematically shows a schematic diagram of a mutation operation on the arrangement order of one sequence according to an embodiment of the present disclosure.
As shown in fig. 9, the sequences are arranged in the order of 5, 2, 4, 3 and 1, wherein the numbers 1, 2, 3, 4 and 5 characterize different classes. The substitution of the species arranged at different positions in the same sequence may be carried out by substituting positions 2 and 4. Thereby obtaining a sequence with the changed arrangement order, wherein the arrangement order is 5, 4, 2, 3 and 1.
In operation S218, the categories corresponding to the slots in the warehouse are reconfigured according to the sequence of the sequence after the sequence is changed and the slot space required by each category.
According to the embodiment of the disclosure, by performing variation operation on the arrangement sequence of one sequence, sequences with different arrangement sequences can be continuously generated, that is, the arrangement sequence of the article types can be changed, so that the article types of the storage positions are reconfigured, and the technical effect of reasonably arranging the storage positions of the warehouse is achieved.
Fig. 10 schematically illustrates a flow chart of a configuration method for warehouse bays according to another embodiment of the present disclosure.
As shown in fig. 10, the method includes operations S219 to S221.
In operation S219, a plurality of sequences with different permutation orders are grouped to obtain a plurality of sets of sequences, where each set of sequences includes one or more sequences.
According to an embodiment of the present disclosure, a plurality of sequences having different arrangement orders may be grouped into a population as a plurality of individuals in the population in a genetic algorithm. Grouping a plurality of sequences having different permutation orders can be, for example, dividing a genetic population into a plurality of sub-populations, with parallel processing between the sub-populations. The sub-populations are quickly iterated internally to achieve information sharing, and the whole population is iterated externally in a small quantity, so that information among the sub-populations can be shared.
In operation S220, a third target sequence is respectively determined from each group of sequence sets in parallel, resulting in a plurality of third target sequences.
According to the embodiment of the disclosure, each group of sequence sets such as a genetic sub-population, and one or more sequences such as one or more individuals in the sub-population, each sub-population can be conveniently internally subjected to selection operation, crossover operation, mutation operation and the like. The results can be evaluated after combining data such as warehouse data, order data, picking data and the like, so that the sub-population is optimized through continuous iteration.
In operation S221, a corresponding bin is configured for each of the multiple categories in parallel according to the arrangement order of each of the multiple third target sequences and the required bin space for each category.
After obtaining the plurality of sets of sequence sets, a target sequence may be determined from each set of sequence sets in parallel by using the method for parallelizing a plurality of sub-populations, and a corresponding bit may be configured for each of the plurality of categories in parallel according to the arrangement order of each target sequence.
FIG. 11 schematically shows a flow diagram for parallelizing processing of multiple sub-populations according to an embodiment of the disclosure.
As shown in fig. 11, in operation S222, a population is divided into a plurality of sub-populations.
In operation S223, the individuals are initialized in parallel.
According to the embodiment of the disclosure, parallelization can be realized by using a Spark tool, and the specific method can be that the original genetic population is divided into a plurality of sub-populations which are parallel to each other, so that the operation efficiency of the algorithm is accelerated.
In operation S224, training iteration is performed inside the sub-population, and operations such as selection operation, crossover operation, mutation operation, and the like can be conveniently performed inside the sub-population. Warehouse data, order data and picking data are pushed to each node in a broadcast mode, results can be evaluated after the warehouse data, the order data, the picking data and the like are combined, population is optimized through continuous iteration, and the iteration times need manual designation. This series of operations may be processed in parallel.
In operation S225, the sub-populations are randomly shuffled. All individuals in all the sub-populations are randomly disorganized and are re-partitioned, namely, new sub-populations are regenerated, so that information sharing among all the populations is realized, and external iteration of the populations is realized.
According to the embodiment of the disclosure, the external iteration can be realized by randomly disordering all individuals in all the sub-populations and re-partitioning, namely, regenerating new sub-populations by using a RDD repartion method, so that information sharing among the populations is realized, and the algorithm is prevented from being premature. Since each iteration generates a new RDD from the old RDD, and mapPartition is a transformation operator lazy execution, the persistence method of RDD can be used to persist data after each iteration.
In operation S226, after iterating the training within the sub-population and randomly scrambling the sub-population, it is determined whether the algorithm converges.
In operation S227, if the convergence is reached, the result is output, the optimal sub-population is output, the arrangement order of the individuals is obtained, and the categories corresponding to the warehouse storage locations are configured according to the arrangement order of the individuals. And if not, repeating the training iteration in the sub-population.
According to the embodiment of the disclosure, the warehouse item class layout problem is abstracted into a queuing problem, and one sequencing sequence is a solution of the item class sequence corresponding to the warehouse storage position, so that the problem is solved by using a genetic algorithm. The population of the genetic algorithm is automatically divided into sub-populations, and the iteration of the genetic algorithm is divided into internal iteration and external iteration, so that the information sharing is realized while the efficiency is improved in parallel, and the algorithm is prevented from being premature.
Fig. 12 schematically illustrates a block diagram of a configuration system for warehouse bays, in accordance with an embodiment of the present disclosure.
As shown in fig. 12, the configuration system 400 of the warehouse depot includes a first acquisition module 401, a second acquisition module 402, a first determination module 403, a sorting module 404, and a first configuration module 405.
The first obtaining module 401 is configured to obtain order data, where the order data relates to a plurality of orders of a plurality of categories.
The second obtaining module 402 is used for obtaining the bin data of the warehouse and the attribute information of each of the multiple categories.
The first determining module 403 is configured to determine a bin space required by each of the categories according to the bin data of the warehouse and the attribute information of each of the categories.
The sorting module 404 is configured to sort the multiple categories related to the order data to obtain multiple sequences with different sorting orders.
The first configuration module 405 is configured to configure a corresponding storage for each category according to an arrangement order of a first target sequence in the plurality of sequences and a storage space required by each category.
Fig. 13 schematically illustrates a block diagram of a first configuration module according to an embodiment of the disclosure.
As shown in fig. 13, the first configuration module 405 includes a first determination unit 4051 and a second determination unit 4052.
The first determining unit 4051 is configured to determine a picking distance of each order in the order data according to the arrangement order of the first target sequence and the space of the storage space required by each category, wherein the picking distance is a length of a path through which goods in the order are picked according to a picking path, and the picking path is determined according to the storage space initially configured for each category.
The second determination unit 4052 is configured to determine whether to reconfigure the category corresponding to the storage position in the warehouse based on the picking distance of each of the plurality of orders.
Fig. 14 schematically shows a block diagram of a second determination unit according to an embodiment of the present disclosure.
As shown in fig. 14, the second determination unit 4052 includes a calculation subunit 40521, a determination subunit 40522, and a configuration subunit 40523.
The calculating sub-unit 40521 is configured to sum the picking distance of each order in the plurality of orders to obtain a calculation result.
The determination sub-unit 40522 is configured to re-determine the second target sequence from among the plurality of sequences having different arrangement orders, in a case where the calculation result does not satisfy the preset condition.
The configuration subunit 40523 is configured to reconfigure the categories corresponding to the storage locations in the warehouse according to the re-determined arrangement order of the second target sequence and the storage location space required by each category.
Fig. 15 schematically illustrates a block diagram of a configuration system for warehouse bays, according to another embodiment of the present disclosure.
As shown in fig. 15, the configuration system 400 of the warehouse storage location further includes a second determination module 406, a third determination module 407, a first exchange module 408, and a second configuration module 409.
The second determining module 406 is configured to randomly determine two sequences from a plurality of sequences having different permutation orders.
The third determining module 407 is configured to determine whether a crossover operation needs to be performed on the arrangement order of the two sequences, where the crossover operation is configured to swap the categories arranged at the corresponding positions of the two sequences to change the arrangement order of the two sequences.
The first exchanging module 408 is configured to exchange the categories arranged at the corresponding positions of the two sequences to obtain the two sequences with the changed arrangement order when the arrangement order of the two sequences needs to be crossed.
The second configuration module 409 is configured to reconfigure the categories corresponding to the storage positions in the warehouse according to the arrangement order of the two sequences after changing the arrangement order and the storage position space required by each category.
Fig. 16 schematically illustrates a block diagram of a configuration system for warehouse bays, according to another embodiment of the present disclosure.
As shown in fig. 16, the configuration system 400 of the warehouse storage further includes a fourth determination module 410, a fifth determination module 411, a second exchange module 412, and a third configuration module 413.
The fourth determining module 410 is configured to randomly determine a sequence from a plurality of sequences having different permutation orders.
The fifth determining module 411 is configured to determine whether a mutation operation is required to be performed on the arrangement order of a sequence, wherein the mutation operation is configured to swap the articles arranged at different positions of a sequence to change the arrangement order of a sequence.
The second exchanging module 412 is configured to exchange the categories arranged at different positions of a sequence to obtain a sequence with a changed arrangement order when a variation operation needs to be performed on the arrangement order of the sequence.
The third configuration module 413 is configured to reconfigure the categories corresponding to the storage locations in the warehouse according to the arrangement order of the sequence after changing the arrangement order and the storage location space required by each category.
Fig. 17 schematically illustrates a block diagram of a configuration system for warehouse bays, according to another embodiment of the present disclosure.
As shown in fig. 17, the configuration system 400 of warehouse bays further includes a grouping module 414, a sixth determining module 415, and a fourth configuring module 416.
The grouping module 414 is configured to group a plurality of sequences with different permutation sequences to obtain a plurality of sets of sequences, where each set of sequences includes one or more sequences.
The sixth determining module 415 is configured to determine a third target sequence from each group of sequence sets in parallel, respectively, to obtain a plurality of third target sequences.
The fourth configuring module 416 is configured to configure a corresponding storage bit for each of the multiple categories in parallel according to the arrangement order of each of the multiple third target sequences and the storage bit space required by each category.
According to the embodiment of the disclosure, because the class layout problem corresponding to the storage positions of the warehouse is abstracted as the sorting problem, one sorting sequence is a solution of the class sequence corresponding to the storage positions of the warehouse, and the corresponding storage positions are configured for each class according to the arrangement sequence of the first target sequence in the sequences and the storage position space required by each class, rather than being sequentially stored along the picking sequence of the storage positions of the warehouse according to the sorting of the goods sales volume from large to small, the technical problem of low picking efficiency caused by longer picking path due to the fact that the warehouse layout scheme in the related technology is at least partially overcome, and the technical effects of reducing the picking distance and improving the picking work efficiency of the warehouse are achieved.
According to an embodiment of the present disclosure, the order picking path of the orders may be determined according to an order of arrangement of the first target sequence in the plurality of sequences, and whether to reconfigure the category corresponding to the stock level in the warehouse may be determined based on the picking distance of each order in the plurality of orders such that, after reconfiguring the category corresponding to the stock level in the warehouse, a sum of the reconfigured picking distances of each order in the plurality of orders is smaller than a sum of the picking distances of each order in the plurality of orders before reconfiguring the stock level in the warehouse, whereby the categories corresponding to the stock level in the warehouse may be continuously reconfigured until the sum of the reconfigured picking distances of each order in the plurality of orders reaches a preset condition, for example, until the sum of the reconfigured picking distances of each order in the plurality of orders reaches a minimum or is smaller than or equal to a threshold value, and the like. Therefore, the technical problems that the picking path is long and the picking efficiency is low due to the fact that the warehouse layout scheme in the related technology is partially overcome, the picking distance is reduced, the warehouse picking work efficiency is improved, meanwhile, the requirements of upstream and downstream of a supply chain can be met, the logistics transportation efficiency is improved, and the technical effect of reasonable layout of storage positions of the warehouse is achieved.
Any number of modules, sub-modules, units, sub-units, or at least part of the functionality of any number thereof according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, and sub-units according to the embodiments of the present disclosure may be implemented by being split into a plurality of modules. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented at least in part as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented in any other reasonable manner of hardware or firmware by integrating or packaging a circuit, or in any one of or a suitable combination of software, hardware, and firmware implementations. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the disclosure may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.
For example, any plurality of the first obtaining module 401, the second obtaining module 402, the first determining module 403, the sorting module 404 and the first configuring module 405 may be combined and implemented in one module/unit/sub-unit, or any one of the modules/units/sub-units may be split into a plurality of modules/units/sub-units. Alternatively, at least part of the functionality of one or more of these modules/units/sub-units may be combined with at least part of the functionality of other modules/units/sub-units and implemented in one module/unit/sub-unit. According to an embodiment of the present disclosure, at least one of the first obtaining module 401, the second obtaining module 402, the first determining module 403, the ordering module 404, and the first configuring module 405 may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or implemented by any one of three implementations of software, hardware, and firmware, or by a suitable combination of any several of them. Alternatively, at least one of the first obtaining module 401, the second obtaining module 402, the first determining module 403, the ordering module 404 and the first configuring module 405 may be at least partly implemented as a computer program module, which when executed may perform a corresponding function.
FIG. 18 schematically illustrates a block diagram of a computer system suitable for implementing the above-described method, in accordance with an embodiment of the present disclosure. The computer system illustrated in FIG. 18 is only one example and should not impose any limitations on the scope of use or functionality of embodiments of the disclosure.
As shown in fig. 18, a computer system 500 according to an embodiment of the present disclosure includes a processor 501, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. The processor 501 may comprise, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 501 may also include onboard memory for caching purposes. Processor 501 may include a single processing unit or multiple processing units for performing different actions of a method flow according to embodiments of the disclosure.
In the RAM 503, various programs and data necessary for the operation of the system 500 are stored. The processor 501, the ROM 502, and the RAM 503 are connected to each other by a bus 504. The processor 501 performs various operations of the method flows according to the embodiments of the present disclosure by executing programs in the ROM 502 and/or the RAM 503. Note that the programs may also be stored in one or more memories other than the ROM 502 and the RAM 503. The processor 501 may also perform various operations of method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.
According to an embodiment of the present disclosure, system 500 may also include an input/output (I/O) interface 505, input/output (I/O) interface 505 also being connected to bus 504. The system 500 may also include one or more of the following components connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.
According to embodiments of the present disclosure, method flows according to embodiments of the present disclosure may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable storage medium, the computer program containing program code for performing the method illustrated by the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511. The computer program, when executed by the processor 501, performs the above-described functions defined in the system of the embodiments of the present disclosure. The systems, devices, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer readable medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.
According to embodiments of the present disclosure, a computer-readable storage medium may be a computer-readable signal medium or a computer-readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable storage medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, optical fiber cable, radio frequency signals, etc., or any suitable combination of the foregoing.
For example, according to embodiments of the present disclosure, a computer-readable storage medium may include ROM 502 and/or RAM 503 and/or one or more memories other than ROM 502 and RAM 503 described above.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.
The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.

Claims (14)

1. A configuration method for warehouse bays, comprising:
obtaining order data, wherein the order data relates to a plurality of orders of a plurality of categories;
acquiring storage position data of a warehouse and attribute information of each of the multiple categories;
determining a storage space required by each category according to the storage data of the warehouse and the attribute information of each category;
sorting the multiple categories related to the order data to obtain multiple sequences with different sorting sequences; and
and configuring a corresponding storage position for each category according to the arrangement sequence of the first target sequence in the plurality of sequences and the storage position space required by each category.
2. The method of claim 1, wherein configuring the corresponding bin for each category according to the arrangement order of the first target sequence in the plurality of sequences and the required bin space of the each category comprises:
determining a picking distance of each order in the order data according to the arrangement sequence of the first target sequence and the storage space required by each category, wherein the picking distance is the length of a path for picking the goods in the order according to a picking path, and the picking path is determined according to the storage space initially configured for each category; and
determining whether to reconfigure the class corresponding to the bin in the warehouse based on the picking distance of each of the plurality of orders.
3. The method of claim 2, wherein determining whether to reconfigure the categories corresponding to the bins in the warehouse based on the picking distance for each of the plurality of orders comprises:
adding and calculating the picking distance of each order in the plurality of orders to obtain a calculation result;
under the condition that the calculation result does not meet the preset condition, re-determining a second target sequence from the sequences with different arrangement orders; and
and reconfiguring the categories corresponding to the storage positions in the warehouse according to the re-determined arrangement sequence of the second target sequence and the storage position space required by each category.
4. The method of claim 1, wherein the method further comprises:
randomly determining two sequences from the plurality of sequences having different arrangement orders;
determining whether a crossover operation is required to be performed on the arrangement order of the two sequences, wherein the crossover operation is used for exchanging the articles arranged at the corresponding positions of the two sequences so as to change the arrangement order of the two sequences;
under the condition that the arrangement sequence of the two sequences needs to be subjected to cross operation, exchanging the categories arranged at the corresponding positions of the two sequences to obtain two sequences with the arrangement sequence changed; and
and reconfiguring the categories corresponding to the storage positions in the warehouse according to the arrangement sequence of the two sequences after the arrangement sequence is changed and the storage position space required by each category.
5. The method of claim 1, wherein the method further comprises:
randomly determining a sequence from the plurality of sequences having different arrangement orders;
determining whether a mutation operation is required to be performed on the arrangement order of the one sequence, wherein the mutation operation is used for exchanging the categories arranged at different positions of the one sequence so as to change the arrangement order of the one sequence;
under the condition that the variation operation needs to be carried out on the arrangement sequence of the sequence, exchanging the varieties arranged at different positions of the sequence to obtain a sequence with the arrangement sequence changed; and
and reconfiguring the categories corresponding to the storage positions in the warehouse according to the arrangement sequence of the sequence after the arrangement sequence is changed and the storage position space required by each category.
6. The method of claim 1, wherein the method further comprises:
grouping the sequences with different arrangement sequences to obtain a plurality of groups of sequence sets, wherein each group of sequence sets comprises one or more sequences;
respectively determining a third target sequence from each group of sequence sets in parallel to obtain a plurality of third target sequences; and
and configuring a corresponding storage position for each of the multiple categories in parallel according to the arrangement sequence of each of the multiple third target sequences and the storage position space required by each category.
7. A configuration system for a warehouse depot, comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring order data, and the order data relates to a plurality of orders of a plurality of categories;
the second acquisition module is used for acquiring the storage position data of the warehouse and the attribute information of each of the multiple categories;
the first determining module is used for determining the storage space required by each category according to the storage position data of the warehouse and the attribute information of each category;
the ordering module is used for ordering the various categories related to the order data to obtain a plurality of sequences with different ordering sequences; and
and the first configuration module is used for configuring a corresponding storage position for each category according to the arrangement sequence of the first target sequence in the plurality of sequences and the storage position space required by each category.
8. The system of claim 7, wherein the first configuration module comprises:
a first determining unit, configured to determine a picking distance of each order in the order data according to the arrangement order of the first target sequence and the storage space required by each category, where the picking distance is a path length through which items in the order are picked according to a picking path, and the picking path is determined according to the storage space initially configured for each category; and
a second determining unit, configured to determine whether to reconfigure the category corresponding to the storage position in the warehouse based on the picking distance of each of the plurality of orders.
9. The system of claim 8, wherein the second determination unit comprises:
the calculation subunit is used for summing the picking distance of each order in the plurality of orders to obtain a calculation result;
a determining subunit, configured to re-determine a second target sequence from the plurality of sequences with different arrangement orders if the calculation result does not satisfy a preset condition; and
and the configuration subunit is used for reconfiguring the categories corresponding to the storage positions in the warehouse according to the re-determined arrangement sequence of the second target sequence and the storage position space required by each category.
10. The system of claim 7, wherein the system further comprises:
a second determining module for randomly determining two sequences from the plurality of sequences having different permutation orders;
a third determining module, configured to determine whether a crossover operation needs to be performed on the arrangement order of the two sequences, where the crossover operation is used to swap the categories arranged at corresponding positions of the two sequences to change the arrangement order of the two sequences;
the first exchange module is used for exchanging the categories arranged at the corresponding positions of the two sequences under the condition that the arrangement sequence of the two sequences needs to be subjected to cross operation, so as to obtain the two sequences with the changed arrangement sequence; and
and the second configuration module is used for reconfiguring the categories corresponding to the storage positions in the warehouse according to the arrangement sequence of the two sequences after the arrangement sequence is changed and the storage position space required by each category.
11. The system of claim 7, wherein the system further comprises:
a fourth determining module, configured to randomly determine a sequence from the plurality of sequences with different permutation orders;
a fifth determining module, configured to determine whether a variation operation needs to be performed on the permutation order of the one sequence, where the variation operation is configured to swap the categories arranged at different positions of the one sequence to change the permutation order of the one sequence;
the second exchange module is used for exchanging the varieties arranged at different positions of the sequence under the condition that the variation operation needs to be carried out on the arrangement sequence of the sequence to obtain a sequence with the arrangement sequence changed; and
and the third configuration module is used for reconfiguring the categories corresponding to the storage positions in the warehouse according to the arrangement sequence of the sequence after the arrangement sequence is changed and the storage position space required by each category.
12. The system of claim 7, wherein the system further comprises:
the grouping module is used for grouping the sequences with different arrangement sequences to obtain a plurality of groups of sequence sets, wherein each group of sequence sets comprises one or more sequences;
a sixth determining module, configured to determine a third target sequence from each group of sequence sets in parallel, to obtain multiple third target sequences; and
and the fourth configuration module is used for configuring corresponding storage positions for each of the multiple categories in parallel according to the arrangement sequence of each third target sequence in the multiple third target sequences and the storage position space required by each category.
13. A computer system, comprising:
one or more processors;
a memory for storing one or more programs,
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the configuration method for warehouse storage according to any of claims 1 to 6.
14. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to carry out the method of configuring a warehouse bin of any of claims 1 to 6.
CN201810720612.6A 2018-06-29 2018-06-29 Configuration method and system for warehouse storage position Active CN110659760B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201810720612.6A CN110659760B (en) 2018-06-29 2018-06-29 Configuration method and system for warehouse storage position

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201810720612.6A CN110659760B (en) 2018-06-29 2018-06-29 Configuration method and system for warehouse storage position

Publications (2)

Publication Number Publication Date
CN110659760A true CN110659760A (en) 2020-01-07
CN110659760B CN110659760B (en) 2023-04-18

Family

ID=69028479

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201810720612.6A Active CN110659760B (en) 2018-06-29 2018-06-29 Configuration method and system for warehouse storage position

Country Status (1)

Country Link
CN (1) CN110659760B (en)

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111738654A (en) * 2020-06-17 2020-10-02 北京京东振世信息技术有限公司 Method, device, equipment and storage medium for generating picking task in internal distribution warehouse-out
CN113496367A (en) * 2020-03-20 2021-10-12 北京京东振世信息技术有限公司 Storage position determining method, device, equipment and computer readable storage medium
CN113627703A (en) * 2020-05-08 2021-11-09 北京京东乾石科技有限公司 Scheduling method and apparatus for mobile device, computer system, and storage medium
CN113762570A (en) * 2020-10-22 2021-12-07 北京京东振世信息技术有限公司 Order picking task order forming method and device
CN117094648A (en) * 2023-10-19 2023-11-21 安徽领云物联科技有限公司 Visual management system of warehouse based on thing networking

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TW201602928A (en) * 2014-07-10 2016-01-16 Pchome Online Inc Warehouse management system
CN106980955A (en) * 2017-03-29 2017-07-25 北京京东尚科信息技术有限公司 Method and apparatus for determining shelf storage space for shelf

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
TW201602928A (en) * 2014-07-10 2016-01-16 Pchome Online Inc Warehouse management system
CN106980955A (en) * 2017-03-29 2017-07-25 北京京东尚科信息技术有限公司 Method and apparatus for determining shelf storage space for shelf

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
李珍萍等: "基于遗传算法的储位优化问题研究", 《物流技术》 *
王彬彬: "电商环境下仓储中心的储位分配策略研究", 《中国优秀博硕士学位论文全文数据库(硕士)经济与管理科学辑》 *

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113496367A (en) * 2020-03-20 2021-10-12 北京京东振世信息技术有限公司 Storage position determining method, device, equipment and computer readable storage medium
CN113627703A (en) * 2020-05-08 2021-11-09 北京京东乾石科技有限公司 Scheduling method and apparatus for mobile device, computer system, and storage medium
CN111738654A (en) * 2020-06-17 2020-10-02 北京京东振世信息技术有限公司 Method, device, equipment and storage medium for generating picking task in internal distribution warehouse-out
CN113762570A (en) * 2020-10-22 2021-12-07 北京京东振世信息技术有限公司 Order picking task order forming method and device
CN117094648A (en) * 2023-10-19 2023-11-21 安徽领云物联科技有限公司 Visual management system of warehouse based on thing networking
CN117094648B (en) * 2023-10-19 2024-01-09 安徽领云物联科技有限公司 Visual management system of warehouse based on thing networking

Also Published As

Publication number Publication date
CN110659760B (en) 2023-04-18

Similar Documents

Publication Publication Date Title
CN110659760B (en) Configuration method and system for warehouse storage position
CN106980955B (en) Method and apparatus for outputting information
CN106875148B (en) Method and device for determining a storage position for an item
CN107103445B (en) Information processing method and device
JP7072054B2 (en) Methods and equipment for sorting cargo
CN110363456B (en) Method and device for putting articles on shelves
CN109472523B (en) Method and device for sorting goods
CN109840648B (en) Method and device for outputting bin information
CN111523977B (en) Method, device, computing equipment and medium for creating wave order set
US10185752B2 (en) Mining association rules in the map-reduce framework
CN108805316A (en) Cargo method for carrying and device
CN109767150B (en) Information pushing method and device
CN111292030A (en) Bin selection method and device and computer readable storage medium
CN112288347A (en) Method, device, server and storage medium for determining route of cold chain distribution
CN108734559A (en) A kind of order processing method and apparatus
CN111178810B (en) Method and device for generating information
CN109840729A (en) Method, system, storage medium and the electronic equipment of hopper positioning
CN110689159A (en) Commodity replenishment method and device
CN115660380B (en) Order processing method and device for picking goods to person
CN114118888A (en) Order ex-warehouse method and device
CN114219545B (en) Data processing method and device
WO2019027564A1 (en) Automated item assortment system
CN110871980B (en) Storage classification method and device
CN109255563B (en) Method and device for determining storage area of article
CN110135772B (en) Method and device for generating information

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant