CN111523977B

CN111523977B - Method, device, computing equipment and medium for creating wave order set

Info

Publication number: CN111523977B
Application number: CN202010329684.5A
Authority: CN
Inventors: 许群合
Original assignee: Beijing Jingdong Zhenshi Information Technology Co Ltd
Current assignee: Beijing Jingdong Zhenshi Information Technology Co Ltd
Priority date: 2020-04-23
Filing date: 2020-04-23
Publication date: 2023-12-08
Anticipated expiration: 2040-04-23
Also published as: CN111523977A

Abstract

The present disclosure provides a method of creating a collection of wave orders, performed by a computing device, the method comprising: acquiring a plurality of to-be-processed orders, wherein each to-be-processed order in the plurality of to-be-processed orders comprises at least one commodity; creating a wave order set based on the commodity similarity among the plurality of to-be-processed orders, wherein the commodity similarity among the to-be-processed orders in the wave order set meets a preset similarity condition; processing the wave order set to obtain summarized information, wherein the summarized information comprises commodity categories in the wave order set and commodity quantity corresponding to the commodity categories; and determining a target storage location of the commodity in the wave order set based on the summarized information so as to acquire the commodity in the wave order set from the target storage location. The present disclosure also provides a creating apparatus of the wave order set, a computing device, and a computer-readable storage medium.

Description

Method, device, computing equipment and medium for creating wave order set

Technical Field

The present disclosure relates to the field of computer technology, and more particularly, to a method of creating a wave order set, a device for creating a wave order set, a computing device, and a computer-readable storage medium.

Background

In many warehouse operations, picking of goods is usually performed according to orders. However, the related art commodity picking process consists in performing a picking operation on an order-by-order basis.

In the process of implementing the disclosed concept, the inventor finds that at least the following problems exist in the related art, in the warehouse operation of the related art, the commodity picking process basically performs positioning, picking operation and the like according to one order, so that a plurality of similar orders of commodities can be picked in one storage place, but because the plurality of similar orders are positioned by one order, the picking efficiency is low.

Disclosure of Invention

In view of this, the present disclosure provides an optimized method for creating a wave order set, an apparatus for creating a wave order set, a computing device, and a computer-readable storage medium.

One aspect of the present disclosure provides a method of creating a set of wave order orders, performed by a computing device, the method comprising: acquiring a plurality of to-be-processed orders, wherein each to-be-processed order in the plurality of to-be-processed orders comprises at least one commodity, creating a wave order set based on commodity similarity among the plurality of to-be-processed orders, wherein the commodity similarity among the to-be-processed orders in the wave order set meets a preset similar condition, processing the wave order set to obtain summarized information, wherein the summarized information comprises commodity types in the wave order set and commodity quantity corresponding to the commodity types, and determining target storage positions of commodities in the wave order set based on the summarized information so as to acquire the commodities in the wave order set from the target storage positions.

According to an embodiment of the present disclosure, the method for processing the commodity similarity between the to-be-processed orders in the wave order set includes: each to-be-processed order in the wave order set is provided with a commodity of a preset category, and the ratio between the category number of the preset category and the category number of each to-be-processed order meets the preset ratio.

According to an embodiment of the present disclosure, the plurality of pending orders includes N pending orders, where N is an integer greater than or equal to 1. Wherein creating the wave order set based on the commodity similarity between the plurality of pending orders comprises: and processing the N to-be-processed orders to obtain an initial target set, wherein the initial target set at least comprises target commodities of the N to-be-processed orders, M to-be-processed orders in the N to-be-processed orders are determined to be the wave order set based on a first contact ratio of each to-be-processed order in the N to-be-processed orders to the initial target set, and the first contact ratio is used for representing the similarity degree of the commodities of each to-be-processed order to the commodities in the initial target set, and M is a positive integer less than or equal to N.

According to an embodiment of the present disclosure, determining M pending orders in the N pending orders based on the first contact ratio between each pending order in the N pending orders and the initial target set includes: calculating a first contact ratio of each of the N to-be-processed orders and the initial target set, and sequentially adding the N to-be-processed orders to the initial target set according to the order of the first contact ratio from large to small to obtain a current target set until the first contact ratio of the currently added to-be-processed orders is smaller than a preset threshold, wherein the to-be-processed orders added to the initial target set are at least one part of the M to-be-processed orders.

According to an embodiment of the present disclosure, determining M pending orders of the N pending orders based on the first contact ratio between each pending order of the N pending orders and the initial target set further includes performing loop execution under a preset condition: calculating a second degree of coincidence between the current target set and the pending orders which are not added to the current target set in the N pending orders, adding the pending orders which are not added to the current target set in sequence from the second degree of coincidence to the small degree, and updating the current target set when the second degree of coincidence is smaller than the preset threshold, wherein the pending orders in the current target set after execution is determined to be the M pending orders.

According to an embodiment of the present disclosure, the above satisfaction of the preset condition includes at least one of: the number of commodities in the current target set is smaller than a target preset number, and the N pending orders are not all added to the current target set.

According to an embodiment of the present disclosure, the updating the current target set includes: and determining a supplementary commodity with the similarity meeting the preset similarity with the commodity in the current target set, and adding the supplementary commodity to the current target set, wherein the distance between the storage position of the supplementary commodity and the storage position of the commodity in the current target set meets the preset distance condition.

According to an embodiment of the present disclosure, the first overlap ratio includes a ratio between a number of first commodity intersections and a number of commodities of each of the N pending orders, where the first commodity intersections are intersections of commodities of each of the N pending orders with commodities in the initial target set, and the second overlap ratio includes a ratio between a number of second commodity intersections and a number of commodities of each of the pending orders that have not been added to the current target set, where the second commodity intersections are intersections of commodities of each of the pending orders that have not been added to the current target set with commodities in the current target set.

According to an embodiment of the present disclosure, the method further includes: processing the to-be-processed orders in the wave order set to obtain K-class commodities and the number of each class of commodities in the K-class commodities, wherein K is an integer greater than or equal to 1, determining at least one storage position of the K-class commodities based on the K-class commodities and the number of each class of commodities in the K-class commodities, and generating a positioning result of each to-be-processed order in the wave order set based on the at least one storage position, wherein the positioning result of each to-be-processed order comprises the storage position of the commodity in the order and the number of the commodity.

According to an embodiment of the present disclosure, the method further includes: and determining that a plurality of to-be-processed orders with consistent storage positions and a sum of commodity numbers being a preset number are spliced orders based on a positioning result of each to-be-processed order in the wave order set, wherein the preset number characterizes the commodity number stored in the storage unit, generating at least one picking task based on the spliced orders, wherein the plurality of to-be-processed orders belonging to the same spliced order belong to one picking task in the at least one picking task, and generating a picking set order based on the at least one picking task so as to execute the picking task based on the picking set order to the corresponding storage position.

According to an embodiment of the present disclosure, the processing the N pending orders to obtain an initial target set includes: and calculating the number of each commodity in the N to-be-processed orders, determining at least one commodity in the N to-be-processed orders as the target commodity based on the number of each commodity in the N to-be-processed orders, wherein the number of each commodity in the at least one commodity is larger than the number of each remaining commodity in the N to-be-processed orders, and adding the target commodity to the initial target set.

Another aspect of the present disclosure provides a creating apparatus for a wave order set, including: the device comprises an acquisition module, a creation module, a first processing module and a first determination module. The acquisition module acquires a plurality of to-be-processed orders, wherein each to-be-processed order in the plurality of to-be-processed orders comprises at least one commodity. The creating module creates a wave order set based on the commodity similarity among the plurality of to-be-processed orders, wherein the commodity similarity among the to-be-processed orders in the wave order set meets a preset similarity condition. The first processing module is used for processing the wave order set to obtain summarized information, wherein the summarized information comprises commodity categories in the wave order set and commodity quantity corresponding to the commodity categories. And the first determining module is used for determining a target storage position of the commodity in the wave order set based on the summarized information so as to acquire the commodity in the wave order set from the target storage position.

According to an embodiment of the present disclosure, the above apparatus further includes: the device comprises a second processing module, a second determining module and a first generating module. The second processing module processes the to-be-processed orders in the wave order set to obtain K types of commodities and the number of each type of commodities in the K types of commodities, wherein K is an integer greater than or equal to 1. And the second determining module is used for determining at least one storage position of the K-class commodities based on the K-class commodities and the quantity of each class of commodities in the K-class commodities. The first generation module generates a positioning result of each to-be-processed order in the wave order set based on the at least one storage position, wherein the positioning result of each to-be-processed order comprises the storage position of the commodity in the order and the commodity quantity.

According to an embodiment of the present disclosure, the above apparatus further includes: the device comprises a third determining module, a second generating module and a third generating module. The third determining module determines that a plurality of pending orders with consistent storage positions and a sum of commodity numbers being a preset number are split orders based on a positioning result of each pending order in the wave order set, wherein the preset number represents the commodity number stored in the storage unit. And the second generation module is used for generating at least one picking task based on the spliced orders, wherein a plurality of pending orders belonging to the same spliced order belong to one picking task in the at least one picking task. And a third generation module for generating a pick collection list based on the at least one pick task so as to execute the pick task based on the pick collection list to a corresponding storage position.

Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions that, when executed, are configured to implement a method as described above.

Another aspect of the present disclosure provides a computer program comprising computer executable instructions which when executed are for implementing a method as described above.

According to the embodiment of the disclosure, the problem that in the related art, commodity picking processes are basically performed according to one order, and picking operations are performed according to one order can be at least partially solved, so that multiple orders with similar commodities can be picked at one storage position, but because multiple orders with similar orders are performed according to one order, multiple picking operations are required, the picking efficiency is low, and therefore the technical effect of improving the picking efficiency can be achieved.

Drawings

The above and other objects, features and advantages of the present disclosure will become more apparent from the following description of embodiments thereof with reference to the accompanying drawings in which:

FIG. 1 schematically illustrates a system architecture of a method of creating a set of wave order and a device of creating a set of wave order according to an embodiment of the present disclosure;

FIG. 2 schematically illustrates a flow chart of a method of creating a collection of wave orders, according to an embodiment of the disclosure;

FIG. 3 schematically illustrates a flow chart of a method of creating a collection of wave orders according to another embodiment of the disclosure;

FIG. 4 schematically illustrates a block diagram of a creating apparatus of a wave order set according to an embodiment of the present disclosure;

FIG. 5 schematically illustrates a block diagram of a creating apparatus of a wave order set according to another embodiment of the present disclosure; and

FIG. 6 schematically illustrates a block diagram of a computer system adapted for creation of a set of wave order according to 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 only exemplary 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 present disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. In addition, in the following description, descriptions of well-known structures and techniques are omitted so as not to 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/or 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 should be noted that the terms used herein should be construed to have meanings consistent with the context of the present specification and should not be construed in an idealized or overly formal manner.

Where expressions like at least one of "A, B and C, etc. are used, the expressions should generally be interpreted in accordance with the meaning as commonly understood by those skilled in the art (e.g.," a system having at least one of A, B and C "shall include, but not be limited to, a system having 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 formulation similar to at least one of "A, B or C, etc." is used, in general such a formulation should be interpreted in accordance with the ordinary understanding of one skilled in the art (e.g. "a system with at least one of A, B or C" would include but not be limited to systems with 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.).

Embodiments of the present disclosure provide a method of creating a set of wave order orders, performed by a computing device, the method comprising: acquiring a plurality of to-be-processed orders, wherein each to-be-processed order in the plurality of to-be-processed orders comprises at least one commodity, creating a wave order set based on commodity similarity among the plurality of to-be-processed orders, wherein the commodity similarity among the to-be-processed orders in the wave order set meets a preset similar condition, processing the wave order set to obtain summarized information, wherein the summarized information comprises commodity types in the wave order set and commodity quantity corresponding to the commodity types, and determining target storage positions of commodities in the wave order set based on the summarized information so as to acquire the commodities in the wave order set from the target storage positions.

Fig. 1 schematically illustrates a system architecture of a method of creating a wave order set and a device of creating a wave order set according to an embodiment of the present disclosure. It should be noted that fig. 1 is only an example of a system architecture to which embodiments of the present disclosure may be applied to assist those skilled in the art in understanding the technical content of the present disclosure, but does not mean that embodiments of the present disclosure may not be used in other devices, systems, environments, or scenarios.

As shown in fig. 1, a system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as shopping class applications, web browser applications, search class applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only) may be installed on the terminal devices 101, 102, 103.

The terminal devices 101, 102, 103 may be a variety of electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablets, laptop and desktop computers, and the like.

The server 105 may be a server providing various services, such as a background management server (by way of example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and process the received data such as the user request, and feed back the processing result (e.g., the web page, information, or data obtained or generated according to the user request) to the terminal device.

It should be noted that, the method for creating a wave order set provided by the embodiments of the present disclosure may be generally performed by the server 105. Accordingly, the creation means of the wave order set provided by the embodiments of the present disclosure may be generally provided in the server 105. The method of creating a set of wave orders provided by the embodiments of the present disclosure may also be performed by a server or a cluster of servers other than the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the creation means of the wave order set provided by the embodiments of the present disclosure may also be provided in a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105.

For example, the multiple pending orders of the embodiments of the present disclosure may be stored in the terminal devices 101, 102, 103, the multiple pending orders are sent to the server 105 by the terminal devices 101, 102, 103, the server 105 may create a wave order set based on the commodity similarity between the multiple pending orders, or the terminal devices 101, 102, 103 may also create a wave order set directly based on the commodity similarity between the multiple pending orders. In addition, the plurality of pending orders may also be stored directly in the server 105, creating a set of wave order orders by the server 105 directly based on the similarity of the plurality of pending orders to each other's merchandise.

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 flowchart of a method of creating a collection of wave orders according to an embodiment of the disclosure.

As shown in fig. 2, the method may include, for example, the following operations S210 to S240. Wherein the method may be performed, for example, by a computing device.

In operation S210, a plurality of pending orders are acquired, wherein each of the plurality of pending orders includes at least one commodity.

According to an embodiment of the present disclosure, a plurality of pending orders are stored, for example, in a pool of orders, with the items of each order in the pool of orders being, for example, items waiting to be picked.

In operation S220, a wave order set is created based on the commodity similarities among the plurality of pending orders, wherein the commodity similarities among the pending orders in the wave order set satisfy a preset similarity condition.

According to an embodiment of the present disclosure, the set of wave order includes, for example, a portion of the plurality of pending orders. The commodity categories of the orders to be processed in the wave order set are similar. For example, each of the pending orders in the set of wave order orders has a preset category of merchandise, and a ratio between a category number of the preset category and a category number of each of the pending orders satisfies a preset ratio.

For example, the preset categories include a categories, for example, a to-be-processed order, and the commodity categories in the to-be-processed order are b categories, for example, wherein the ratio between a and b is greater than the preset ratio, for example. The predetermined proportion includes, for example, a predetermined threshold value, i.e., the value of a/b is greater than, for example, the predetermined threshold value.

In the embodiment of the disclosure, in order to check the picking efficiency, the embodiment of the disclosure creates the to-be-processed order with higher similarity of the commodities in the plurality of to-be-processed orders as the wave order set, so that the higher similarity of the commodity types of the to-be-processed orders in the wave order set is realized, and the commodities in all to-be-processed orders in the wave order set can be obtained by acquiring the commodities with fewer commodity types when the picking is performed for the wave order set.

In operation S230, the wave order set is processed to obtain summary information, where the summary information includes a commodity category in the wave order set and a commodity number corresponding to the commodity category. For example, the commodity categories of all pending orders in the set of wave orders may be aggregated and the number of commodities in the set of wave orders corresponding to each commodity category may be determined.

Next, in operation S240, a target storage location of the commodity in the wave order set is determined based on the summary information so as to acquire the commodity in the wave order set from the target storage location.

According to embodiments of the present disclosure, items in a set of wave orders may be located based on summarized information to obtain a target storage location for picking based on the target storage location. The goods in the wave order set can be positioned at the same or adjacent storage positions as much as possible by carrying out positioning based on summarized information, namely, goods in each container positioned are ensured to be used as goods in the wave order set as much as possible.

It can be appreciated that the embodiments of the present disclosure create a wave order set based on the similarity of goods between the orders to be processed, so as to pick the goods based on the wave order set, thereby improving the efficiency of picking the goods. In addition, the wave order sets are summarized to obtain summarized information, positioning is carried out based on the summarized information to obtain positioning results, and sorting is carried out based on the positioning results so as to reduce the times of unpacking.

According to an embodiment of the present disclosure, regarding the commodity similarity between the plurality of pending orders, creating the wave order set in operation S220 may include the following steps (1) to (2), for example.

(1) According to an embodiment of the present disclosure, the plurality of pending orders includes, for example, N pending orders, where N is an integer greater than or equal to 1. And processing the N orders to be processed to obtain an initial target set, wherein the initial target set at least comprises target commodities of the N orders to be processed.

According to the embodiment of the disclosure, since each of the N pending orders includes at least one commodity, the N pending orders include a plurality of commodities. The target commodity may be, for example, at least one of a plurality of commodities. For example, the target commodity may be the largest number of one or more commodities in the plurality of commodities.

After the target commodity is determined, the target commodity may be added to the initial target set. Wherein the initial target set is, for example, an empty set, i.e., the empty set may not include any items, prior to adding the target items to the initial target set.

According to an embodiment of the present disclosure, processing N pending orders to obtain an initial target set includes, for example: the number of each commodity in the N orders to be processed is calculated, and then, at least one commodity in the N orders to be processed is determined as a target commodity based on the number of each commodity in the N orders to be processed. Wherein the number of each commodity in the at least one commodity is greater than the number of each remaining commodity in the N pending orders. That is, one or more items with the most data in the N pending orders are determined as target items. For example, all the products in the N pending orders are arranged from large to small in number, and one or several products arranged in front are determined as target products. The target commodity is then added to the initial target set.

In the embodiment of the disclosure, other commodities with storage positions close to the target commodity can also be added to the initial target set. The other commodities may be, for example, commodities in N orders to be processed, or commodities other than N orders to be processed. It will be appreciated that since the storage location of the other commodity is similar to the target commodity, it may be indicated that the other commodity has a higher similarity to the target commodity. That is, the other commodity and the target commodity may be the same type of commodity. The storage locations may be, for example, logical areas, lanes, reserves, storage locations, etc. in a warehouse.

(2) And determining M to-be-processed orders in the N to-be-processed orders as a wave order set based on a first contact ratio of each to-be-processed order in the N to-be-processed orders and the initial target set, wherein the first contact ratio is used for representing the similarity degree of commodities of each to-be-processed order and commodities in the initial target set, and M is a positive integer less than or equal to N.

According to the embodiment of the disclosure, after the initial target set is determined, each of the N pending orders may be compared with the initial target set, so as to obtain an order in which the commodities in the N pending orders are similar to the commodities in the initial target set. For example, an order of the N pending orders that is similar to the initial target set is determined by calculating a first degree of coincidence of each pending order with the initial target set. Wherein, the higher the first coincidence degree is, the higher the similarity between the order to be processed and the initial target set is. In the implementation of the present disclosure, by calculating the first contact ratio, M pending orders may be determined from N pending orders as a wave order set, so as to perform centralized processing on orders in the wave order set. That is, M pending orders within the one set of wave order may be processed simultaneously. The specific process of determining M pending orders from the N pending orders will be described in detail below.

According to an embodiment of the present disclosure, determining the target storage location of the commodity in the wave order set in the operation S240 based on the summary information may include: and determining target storage positions of the commodities of the M to-be-processed orders so as to acquire the commodities of the M to-be-processed orders from the target storage positions. For example, embodiments of the present disclosure may aggregate the target storage locations for each item in the M pending orders within the collection of wave orders to take the target storage locations as pick destinations.

According to the embodiment of the disclosure, the commodities in the M pending orders in one wave order set have higher similarity, and therefore, the target storage positions of the commodities in the M pending orders are closer, for example. Therefore, the order centralized processing in one wave order set can improve the picking efficiency, namely, all the commodities in the M to-be-processed orders can be acquired from fewer target storage positions, and the picking efficiency is improved.

Typically, for example, the N pending orders include order 1, order 2, order 3, order 4. The order 1 includes, for example, commodity a, commodity B, and commodity C. Order 2 includes, for example, commodity D. Order 3 includes, for example, commodity a, commodity B. Order 4 includes, for example, item E. For example, the storage locations of the products a to E are different, and if the products a to E are picked up according to the order 1, the order 2, the order 3 and the order 4 in order. Then for order 1, for example, 3 storage location pickups are required, for order 2, for example, 1 storage location pickups are required, for order 3, for example, 2 quantity storage location pickups are required, for order 4, for example, 1 storage location pickups are required. And since multiple orders are picked in sequence, the same items in order 1 and order 3 need to be repeatedly picked. In addition, the storage locations for each pick of the same commodity may be different, resulting in multiple needs to disassemble the containers, and the failure to avoid the multiple containers from being disassembled. For example, if each bin had 10 items A, if order 1 included 4 items A, order 3 included 6 items A, removing 4 items A from one bin for order 1 and 6 items from the other bin for order 3 would result in both bins being removed and the removed bins being inconvenient to store.

According to the technical scheme, a plurality of orders which are similar are used as a wave order set, orders in the wave order set are processed in a centralized mode, at least the effects of improving picking and reducing container zero disassembly can be achieved. As depicted in fig. 3 by a specific procedure.

Fig. 3 schematically illustrates a flow chart of a method of creating a set of wave order according to another embodiment of the present disclosure.

As shown in fig. 3, the method includes operations S210 to S240 and operations S310 to S330, for example. Operations S210 to S240 are, for example, the same as or similar to the operations described in fig. 2, and are not described here again.

In operation S310, the order to be processed in the wave order set is processed to obtain K types of commodities and the number of each type of commodities in the K types of commodities, where K is an integer greater than or equal to 1.

In operation S320, at least one storage location of the K-class commodity is determined based on the K-class commodity and the number of each of the K-class commodities.

In operation S330, a positioning result of each pending order in the set of wave order orders is generated based on the at least one storage location, wherein the positioning result of each pending order includes a storage location of the merchandise in the order.

For example, after a similar M of the N pending orders are determined to be a set of wave order orders, all of the items in the M pending orders may be collectively picked.

For example, as illustrated above, continuing with the example where N pending orders include order 1, order 2, order 3, order 4. For example, order 1 and order 3 are determined to be similar M pending orders. The orders 1 and 3 are for example as a collection of wave orders. The order 1 includes, for example, commodity a, commodity B, and commodity C. Order 3 includes, for example, commodity a, commodity B.

Then, the order 1 and the order 3 are processed, and the K types of products obtained include, for example, a product a type, a product B type, and a product C type. Then, the number of products corresponding to each of the product a class, the product B class, and the product C class is determined, for example, the number of products corresponding to the product a class is 10 (4 products a are in order 1, and 6 products a are in order 3). The commodity B is similar to the commodity C and will not be described again. For ease of understanding, the number of products corresponding to the product a is 10 as an example. After determining the number of items corresponding to each type of item, the storage location of each type of item may be further determined. For example, after the number of products corresponding to the product a class is determined to be 10, the storage position of the product a is further determined to be the packing box 1, and the packing box 1 includes, for example, 10 products a. Then, 10 products a in the container 1 can be determined as products of the product a class in the wave order set. For example, the positioning results for order 1 include 4 items A in container 1, and the positioning results for order 3 include 6 items A in container 1. It will be appreciated that embodiments of the present disclosure aggregate the number of items in K categories within a set of wave orders, and then locate the storage locations of the items in the K categories based on the aggregate results, and assign a storage location to each order within the set of wave orders.

It can be appreciated that by the technical scheme of the embodiment of the disclosure, similar orders are determined as a wave order set, and commodity category summarization and positioning are performed in the wave order set, and positioning results are allocated to each order in the wave order set, so that the picking efficiency is greatly improved, and the container zero disassembly is reduced.

According to an embodiment of the present disclosure, after performing operation S330, the method of an embodiment of the present disclosure further includes, for example:

based on the positioning result of each to-be-processed order in the wave order set, a plurality of to-be-processed orders with consistent storage positions and the sum of the commodity numbers being a preset number are determined to be split orders, and the preset number represents the commodity number stored in the storage unit.

For example, the positioning results described above include: the positioning result for the order 1 comprises 4 goods a in the container 1, the positioning result for the order 3 comprises 6 goods a in the container 1, and the positioning result for the order 2 is not repeated. Then, since the storage positions of the commodities in order 1 and order 3 are identical (both are box 1), and the sum of the numbers of commodities a in order 1 and order 3 (the number is 10) is a preset number, for example, the number of commodities stored in the storage unit (one box), order 1 and order 3 can be regarded as one split order. It will be appreciated that a plurality of split orders may be derived from pending orders within a collection of wave orders.

At least one pick task is generated based on the split orders, wherein a plurality of pending orders belonging to the same split order belong to one of the at least one pick task. For example, multiple pending orders within a split order are a pick job, e.g., order 1 and order 3 are a pick job.

Based on the at least one pick job, a pick collection sheet is generated to facilitate performing the pick job based on the pick collection sheet to the corresponding storage location. For example, a plurality of order picking tasks based on the wave order collection can be summarized to obtain a picking collection list, and when picking is performed based on the picking collection list, picking can be performed for each order picking task, so that the picking efficiency is greatly improved, and the cargo box zero-disassembly is reduced.

How to determine M of the N pending orders will be described in detail below.

According to an embodiment of the present disclosure, determining M of the N pending orders as a set of wave order orders based on a first contact ratio of each of the N pending orders with the initial target set includes, for example, the following process.

First, a first contact ratio between each of the N pending orders and the initial target set is calculated. Wherein the first contact ratio comprises, for example, a ratio between the number of first commodity intersections and the number of commodities of each of the N pending orders. The first commodity intersection is the intersection of the commodity of each to-be-processed order in the N to-be-processed orders and the commodity in the initial target set.

For example, one current pending order of the N pending orders is illustrated. The number of commodities to be processed currently is n, for example, the number of commodities in the initial target set is c, for example, and then the number of first commodity intersections is (n c). The first contact ratio C between the current pending order and the initial target set is, for example:

wherein if the first overlap ratio c=1, it indicates that all the commodities in the current pending order are in the initial target set. If the first coincidence C is less than 1, the method indicates that part of commodities in the current pending order are not in the initial target set.

And then adding the N orders to be processed to the initial target set in sequence from the first contact ratio to the small contact ratio to obtain a current target set until the first contact ratio of the currently added orders to be processed is smaller than a preset threshold value. Wherein the pending orders added to the initial target set are at least a portion of the M pending orders.

According to an embodiment of the present disclosure, the first contact ratio being smaller than the preset threshold value may be, for example, the first contact ratio C < 1, that is, the preset threshold value is 1.

For example, the N pending orders include order 1, order 2, order 3, order 4, and so on. Order 1 includes, for example, commodity a. Order 2 includes, for example, commodity B, commodity C. Order 3 includes, for example, commodity C, commodity D. Order 4 includes, for example, item E. The initial target set includes, for example, commodity a and commodity B.

Then, first overlapping ratios of the order 1, the order 2, the order 3 and the order 4 are sequentially calculated, and the first overlapping ratios of the order 1, the order 2, the order 3 and the order 4 are respectively 1, 0.5, 0 and 0. Order 1, order 2, order 3, order 4 are added to the initial target set in order from large to small according to the first overlap ratio. For example, after order 1, order 2 are added in sequence to the initial target set, no more addition is stopped, since the first overlap of the last added order 2 is less than the preset threshold. It will be appreciated that the resulting current target set includes, for example, order 1 and order 2. I.e. the current target set comprises, for example, commodity a, commodity B, commodity C.

Then, the following steps (1) to (3) are cyclically performed under the satisfaction of the preset condition. Wherein, meeting the preset condition includes, for example: the number of commodities in the current target set is smaller than the target preset number, or N pending orders are not all added to the current target set. That is, the embodiment of the present disclosure may circularly perform the following steps (1) to (3) until the number of commodities in the current target set is greater than or equal to the target preset number or N pending orders have all been added to the current target set.

(1) And calculating the second degree of coincidence of the pending orders which are not added to the current target set in the N pending orders and the current target set.

According to an embodiment of the present disclosure, the second degree of overlap includes, for example, a ratio between the number of second item intersections and the number of items of each pending order that have not yet been added to the current target set. The second commodity intersection is the intersection of the commodity of each pending order which is not added to the current target set and the commodity in the current target set. The calculation process of the second contact ratio is the same as or similar to that of the first contact ratio, and will not be described herein.

For example, among the N pending orders, those that have not been added to the current target set include, for example, order 3 and order 4. Order 3 includes, for example, commodity C, commodity D. Order 4 includes, for example, item E. The current target set includes, for example, commodity a, commodity B, commodity C. And respectively calculating the second degree of coincidence of the order 3 and the order 4, and obtaining that the second degree of coincidence of the order 3 and the order 4 is, for example, 0.5 and 0 respectively.

(2) And adding the to-be-processed orders which are not added to the current target set in sequence from the second degree of coincidence to the first degree of coincidence. For example, order 3 is added to the current target set.

(3) And when the second degree of coincidence is smaller than a preset threshold value, updating the current target set, wherein the to-be-processed orders in the current target set after the execution is finished are determined to be M to-be-processed orders.

Since the second degree of overlap of order 3 is less than 1, after order 3 is added to the current target set, no further orders (e.g., order 4) continue to be added to the current target set. At this time, the current target set includes, for example, order 1, order 2, and order 3, that is, the current target set includes commodity a, commodity B, commodity C, and commodity D.

The current target set may then be further updated. For example, a supplemental commodity whose similarity to the commodity in the current target set satisfies a preset similarity may be determined, and the supplemental commodity is added to the current target set. The distance between the storage position of the supplementary commodity and the storage position of the commodity in the current target set meets the preset distance condition.

If the number of commodities in the current target set is greater than or equal to the target preset number, stopping adding orders to the current target set, and taking the orders in the current target set as M to-be-processed orders, wherein the M to-be-processed orders are, for example, a wave order set. If there are remaining orders in the N pending orders that are not added to the current target set, continuing to process the remaining orders to generate a new set of wave order orders. The processing manner of continuing to process the remaining orders is the same as or similar to the processing manner of obtaining the M pending orders, and will not be described here again.

It will be appreciated that after each new order is added to either the initial or current target sets, additional items similar to the new order just added may be added to the current target set in order to update the current target set in real time.

According to an embodiment of the present disclosure, the target preset number is determined, for example, from a set of wave orders over a period of time. For example, an average value of the commodity numbers of a plurality of wave order sets over a period of time is determined as a target preset number. For example, the past period of time may be 7 days, with each of the 7 days having 4 sets of wave orders. Then, the total number of products of all orders for 7 days is determined to be 70000 products, for example, that is, the daily average product number for 7 days is 70000/7=10000. The average value of each wave order set is then calculated to be 10000/4=2500, for example. The average 2500 of the set of wave orders may be, for example, a target preset number.

It will be appreciated that embodiments of the present disclosure determine a set of wave orders that includes multiple orders by determining the degree of coincidence of a pending order with an initial set of targets or a current set of targets. The commodity coincidence degree among a plurality of orders in each wave order set is ensured to be higher, namely the plurality of orders in each wave order set are more similar. Because the orders in each wave order set are similar, the commodity categories in each wave order set are fewer, and the commodity quantity corresponding to each commodity category is larger, so that the picking efficiency is improved, and the container zero-dismantling is reduced. For example, because the commodity similarity in each wave order set is higher, fewer storage positions can be positioned when one wave order set is processed, and the positioning efficiency is improved. By locating fewer storage positions, the picking path is shorter, so that the picking time is shortened, the picking times are reduced, and the picking efficiency is improved.

Fig. 4 schematically shows a block diagram of a creating apparatus of a wave order set according to an embodiment of the present disclosure.

As shown in fig. 4, the creating apparatus 400 for a wave order set includes, for example, an acquiring module 410, a creating module 420, a first processing module 430, and a first determining module 440.

The acquisition module 410 may be configured to acquire a plurality of pending orders, wherein each of the plurality of pending orders includes at least one commodity. According to an embodiment of the present disclosure, the obtaining module 410 may perform, for example, operation S210 described above with reference to fig. 2, which is not described herein.

The creating module 420 may be configured to create a wave order set based on the commodity similarities between the plurality of pending orders, where the commodity similarities between the pending orders in the wave order set satisfy a preset similarity condition. The creation module 420 may, for example, perform operation S220 described above with reference to fig. 2 according to an embodiment of the present disclosure, which is not described herein.

The first processing module 430 may be configured to process the wave order set to obtain summary information, where the summary information includes a commodity category and a commodity number corresponding to the commodity category in the wave order set. According to an embodiment of the present disclosure, the first processing module 430 may, for example, perform the operation S230 described above with reference to fig. 2, which is not described herein.

The first determination module 440 may be configured to determine a target storage location for the items in the set of wave orders based on the aggregated information, such that the items in the set of wave orders are retrieved from the target storage location. According to an embodiment of the present disclosure, the first determining module 440 may perform, for example, operation S240 described above with reference to fig. 2, which is not described herein.

Fig. 5 schematically illustrates a block diagram of a creating apparatus of a wave order set according to another embodiment of the present disclosure.

As shown in fig. 5, the creating apparatus 500 for a wave order set includes, for example, an acquiring module 410, a creating module 420, a first processing module 430, a first determining module 440, a second processing module 510, a second determining module 520, and a first generating module 530. The obtaining module 410, the creating module 420, the first processing module 430, and the first determining module 440 are the same as or similar to the modules described above with reference to fig. 4, and are not described herein.

The second processing module 510 may be configured to process an order to be processed in the wave order set, to obtain K types of commodities and the number of each type of commodities in the K types of commodities, where K is an integer greater than or equal to 1. The second processing module 510 may, for example, perform operation S310 described above with reference to fig. 3 according to an embodiment of the present disclosure, which is not described herein.

The second determining module 520 may be configured to determine at least one storage location of the K-class commodity based on the K-class commodity and the number of each of the K-class commodity. The second determining module 520 may, for example, perform operation S320 described above with reference to fig. 3 according to an embodiment of the present disclosure, which is not described herein.

The first generating module 530 may be configured to generate a positioning result of each pending order in the set of wave order orders based on the at least one storage location, where the positioning result of each pending order includes a storage location of a commodity in the order and a number of commodities. According to an embodiment of the present disclosure, the first generating module 530 may perform, for example, operation S330 described above with reference to fig. 3, which is not described herein.

According to an embodiment of the present disclosure, the satisfaction of the preset similarity condition for the commodity similarity between the to-be-processed orders in the wave order set includes: each to-be-processed order in the wave order set is provided with a commodity of a preset category, and the ratio between the category number of the preset category and the category number of each to-be-processed order meets the preset ratio.

According to an embodiment of the disclosure, the plurality of pending orders includes N pending orders, N being an integer greater than or equal to 1. Wherein creating the wave order set based on the commodity similarity of the plurality of pending orders to each other comprises: processing N to-be-processed orders to obtain an initial target set, wherein the initial target set at least comprises target commodities of the N to-be-processed orders, and determining M to-be-processed orders in the N to-be-processed orders as a wave order set based on first contact ratios of each to-be-processed order in the N to-be-processed orders and the initial target set, wherein the first contact ratios are used for representing similarity degree of commodities of each to-be-processed order and commodities in the initial target set, and M is a positive integer less than or equal to N.

According to an embodiment of the present disclosure, determining M pending orders of the N pending orders based on a first contact ratio of each pending order of the N pending orders with the initial target set includes: calculating the first contact ratio of each of the N to-be-processed orders and the initial target set, and sequentially adding the N to-be-processed orders to the initial target set according to the order of the first contact ratio from large to small to obtain a current target set until the first contact ratio of the currently added to-be-processed orders is smaller than a preset threshold, wherein the to-be-processed orders added to the initial target set are at least one part of the M to-be-processed orders.

According to an embodiment of the present disclosure, determining M of the N pending orders further includes performing, in a loop, on the basis of the first contact ratio of each of the N pending orders with the initial target set, if a preset condition is satisfied: calculating second degree of coincidence between the current target set and the pending orders which are not added to the current target set in the N pending orders, sequentially adding the pending orders which are not added to the current target set according to the sequence from the second degree of coincidence to the first degree, and updating the current target set when the second degree of coincidence is smaller than a preset threshold value, wherein the pending orders in the current target set after the execution is finished are determined to be M pending orders.

According to an embodiment of the present disclosure, satisfying the preset condition includes at least one of: the number of commodities in the current target set is smaller than the target preset number, and N orders to be processed are not added to the current target set.

According to an embodiment of the present disclosure, updating the current target set includes: and determining a supplementary commodity with the similarity meeting the preset similarity with the commodity in the current target set, and adding the supplementary commodity to the current target set, wherein the distance between the storage position of the supplementary commodity and the storage position of the commodity in the current target set meets the preset distance condition.

According to an embodiment of the present disclosure, the first overlap ratio includes a ratio between a number of first commodity intersections, which are intersections of commodities of each of the N pending orders with commodities in the initial target set, and a number of commodity intersections, which are intersections of commodities of each of the N pending orders with commodities in the current target set, which are commodities of each of the pending orders that have not yet been added to the current target set.

According to an embodiment of the present disclosure, the apparatus 400 or 500 may further include, for example: the device comprises a third determining module, a second generating module and a third generating module. The third determining module determines that a plurality of to-be-processed orders with consistent storage positions and the sum of the commodity numbers being a preset number are split orders based on the positioning result of each to-be-processed order in the wave order set, wherein the preset number represents the commodity number stored in the storage unit. And the second generation module is used for generating at least one picking task based on the spliced orders, wherein a plurality of pending orders belonging to the same spliced order belong to one picking task of the at least one picking task. And a third generation module for generating a pick collection list based on the at least one pick task so as to perform the pick task based on the pick collection list to the corresponding storage location.

According to an embodiment of the present disclosure, processing N pending orders, obtaining an initial target set includes: and calculating the quantity of each commodity in the N to-be-processed orders, determining at least one commodity in the N to-be-processed orders as a target commodity based on the quantity of each commodity in the N to-be-processed orders, wherein the quantity of each commodity in the at least one commodity is larger than the quantity of each remaining commodity in the N to-be-processed orders, and adding the target commodity to the initial target set.

Any number of modules, sub-modules, units, sub-units, or at least some of the functionality of any number of the sub-units according to embodiments of the present disclosure may be implemented in one module. Any one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be implemented as split into multiple 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-chip, a system-on-substrate, a system-on-package, an Application Specific Integrated Circuit (ASIC), or in any other reasonable manner of hardware or firmware that integrates or encapsulates the circuit, or in any one of or a suitable combination of three of software, hardware, and firmware. Alternatively, one or more of the modules, sub-modules, units, sub-units according to embodiments of the present disclosure may be at least partially implemented as computer program modules, which when executed, may perform the corresponding functions.

For example, any of the acquisition module 410, the creation module 420, the first processing module 430, the first determination module 440, the second processing module 510, the second determination module 520, and the first generation module 530 may be combined in one module to be implemented, or any of the modules may be split into a plurality of modules. Alternatively, at least some of the functionality of one or more of the modules may be combined with at least some of the functionality of other modules and implemented in one module. According to embodiments of the present disclosure, at least one of the acquisition module 410, the creation module 420, the first processing module 430, the first determination module 440, the second processing module 510, the second determination module 520, and the first generation module 530 may be implemented at least in part as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system-on-chip, a system-on-substrate, a system-on-package, an Application Specific Integrated Circuit (ASIC), or may be implemented in hardware or firmware in any other reasonable manner of integrating or packaging the circuitry, or in any one of or a suitable combination of three of software, hardware, and firmware. Alternatively, at least one of the acquisition module 410, the creation module 420, the first processing module 430, the first determination module 440, the second processing module 510, the second determination module 520, and the first generation module 530 may be at least partially implemented as a computer program module, which when executed may perform the corresponding functions.

FIG. 6 schematically illustrates a block diagram of a computer system adapted for creation of a set of wave order according to an embodiment of the present disclosure. The computer system illustrated in fig. 6 is merely an example and should not be construed as limiting the functionality and scope of use of the embodiments of the present disclosure.

As shown in fig. 6, a computer system 600 according to an embodiment of the present disclosure includes a processor 601 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage section 606 into a Random Access Memory (RAM) 603. The processor 601 may include, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or an associated chipset and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), or the like. Processor 601 may also include on-board memory for caching purposes. The processor 601 may comprise a single processing unit or a plurality of processing units for performing different actions of the method flows according to embodiments of the disclosure.

In the RAM 603, various programs and data required for the operation of the system 600 are stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. The processor 601 performs various operations of the method flow according to the embodiments of the present disclosure by executing programs in the ROM 602 and/or the RAM 603. Note that the program may be stored in one or more memories other than the ROM 602 and the RAM 603. The processor 601 may also perform various operations of the method flow 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, the system 600 may further include an input/output (I/O) interface 605, the input/output (I/O) interface 605 also being connected to the bus 604. The system 600 may also include one or more of the following components connected to the I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; an output portion 607 including a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, a speaker, and the like; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed as needed on drive 610 so that a computer program read therefrom is installed as needed into storage section 608.

According to embodiments of the present disclosure, the method flow according to embodiments of the present disclosure may be implemented as a computer software program. 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 comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611. The above-described functions defined in the system of the embodiments of the present disclosure are performed when the computer program is executed by the processor 601. The systems, devices, apparatus, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the disclosure.

The present disclosure also provides a computer-readable storage medium that may be embodied in the apparatus/device/system described in the above embodiments; or may exist alone without being assembled into the apparatus/device/system. The computer-readable storage medium carries one or more programs which, when executed, implement methods in accordance with embodiments of the present disclosure.

According to embodiments of the present disclosure, the computer-readable storage medium may be a computer-non-volatile computer-readable storage medium, which may include, for example, but is not limited to: 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), 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 context of this 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.

For example, according to embodiments of the present disclosure, the computer-readable storage medium may include ROM 602 and/or RAM 603 and/or one or more memories other than ROM 602 and RAM 603 described above.

The flowcharts 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 the features recited in the various embodiments of the disclosure and/or in the claims may be combined in various combinations and/or combinations, even if such combinations or combinations are not explicitly recited in the disclosure. In particular, the features recited in the various embodiments of the present disclosure and/or the claims may be variously combined and/or combined without departing from the spirit and teachings of the present disclosure. All such combinations and/or combinations fall within the scope of the present disclosure.

The embodiments of the present disclosure are 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 above separately, this does not mean that the measures in the embodiments cannot be used advantageously in combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be made by those skilled in the art without departing from the scope of the disclosure, and such alternatives and modifications are intended to fall within the scope of the disclosure.

Claims

1. A method of creating a collection of wave orders, performed by a computing device, the method comprising:

acquiring a plurality of to-be-processed orders, wherein each to-be-processed order in the plurality of to-be-processed orders comprises at least one commodity;

creating a wave order set based on the commodity similarity among the plurality of to-be-processed orders, wherein the commodity similarity among the to-be-processed orders in the wave order set meets a preset similarity condition;

processing the wave order set to obtain summarized information, wherein the summarized information comprises commodity categories in the wave order set and commodity quantity corresponding to the commodity categories; and

Determining a target storage position of the commodity in the wave order set based on the summarized information, and positioning the commodity in the wave order set at the same or adjacent storage positions so as to acquire the commodity in the wave order set from the target storage position;

wherein the plurality of orders to be processed comprises N orders to be processed, N is an integer greater than or equal to 1;

wherein creating the wave order set based on the commodity similarity between the plurality of pending orders comprises:

processing the N orders to be processed to obtain an initial target set, wherein the initial target set at least comprises target commodities of the N orders to be processed, the target commodities are one or more commodities with the largest quantity in a plurality of commodities, and the initial target set comprises other commodities with storage positions close to the target commodities;

and determining M to-be-processed orders in the N to-be-processed orders as the wave order set based on a first contact ratio of each to-be-processed order in the N to-be-processed orders and the initial target set, wherein the first contact ratio is used for representing the similarity degree of commodities of each to-be-processed order and the commodities in the initial target set, and M is a positive integer less than or equal to N.

2. The method of claim 1, wherein the commodity similarity between the pending orders in the set of wave orders meeting a preset similarity condition comprises:

each to-be-processed order in the wave order set is provided with a commodity of a preset category, and the ratio between the category number of the preset category and the category number of each to-be-processed order meets the preset ratio.

3. The method of claim 1, wherein the determining M of the N pending orders based on the first degree of coincidence of each of the N pending orders with the initial target set comprises:

calculating a first contact ratio of each to-be-processed order in the N to-be-processed orders and the initial target set; and

sequentially adding N to-be-processed orders to the initial target set according to the order of the first contact ratio from large to small to obtain a current target set until the first contact ratio of the currently added to-be-processed orders is smaller than a preset threshold value,

wherein the pending orders added to the initial target set are at least a portion of the M pending orders.

4. The method of claim 3, wherein determining M of the N pending orders based on the first degree of coincidence of each of the N pending orders with the initial target set further comprises performing a loop if a preset condition is met:

Calculating a second degree of coincidence between the current target set and the pending orders which are not added to the current target set in the N pending orders;

sequentially adding the to-be-processed orders which are not added to the current target set according to the order of the second contact ratio from large to small; and

updating the current target set when the second degree of coincidence is less than the preset threshold value,

and determining the to-be-processed orders in the current target set after the execution is finished as the M to-be-processed orders.

5. The method of claim 4, wherein the satisfaction of the preset condition comprises at least one of:

the number of commodities in the current target set is smaller than the target preset number; and

the N pending orders have not all been added to the current target set.

6. The method of claim 4, wherein the updating the current target set comprises:

determining supplementary commodities, the similarity of which with the commodities in the current target set meets preset similarity; and

adding the supplemental good to the current target set,

the distance between the storage position of the supplementary commodity and the storage position of the commodity in the current target set meets the preset distance condition.

7. The method according to claim 4, wherein:

the first overlap ratio comprises a ratio between the number of first commodity intersections and the number of commodities of each of the N to-be-processed orders, wherein the first commodity intersections are intersections of the commodities of each of the N to-be-processed orders and the commodities in the initial target set; and

the second degree of overlap includes a ratio between a number of second commodity intersections, which are intersections of the commodities of each pending order that has not been added to the current target set with the commodities in the current target set, and a number of commodities of each pending order that has not been added to the current target set.

8. The method of claim 1, further comprising:

processing an order to be processed in the wave order set to obtain K types of commodities and the number of each type of commodities in the K types of commodities, wherein K is an integer greater than or equal to 1;

determining at least one storage position of the K-class commodity based on the K-class commodity and the number of each class of commodity in the K-class commodity; and

and generating a positioning result of each to-be-processed order in the wave order set based on the at least one storage position, wherein the positioning result of each to-be-processed order comprises the storage position of the commodity in the order and the commodity quantity.

9. The method of claim 8, further comprising:

determining that a plurality of to-be-processed orders with consistent storage positions and the sum of commodity numbers being preset numbers are split orders based on the positioning result of each to-be-processed order in the wave order set, wherein the preset numbers represent the commodity numbers stored in a storage unit;

generating at least one picking task based on the split orders, wherein a plurality of pending orders belonging to the same split order belong to one of the at least one picking task; and

based on the at least one pick job, a pick collection sheet is generated to facilitate performing the pick job based on the pick collection sheet to a corresponding storage location.

10. The method of claim 2, wherein the processing the N pending orders to obtain an initial target set comprises:

calculating the quantity of each commodity in the N orders to be processed;

determining at least one commodity in the N to-be-processed orders as the target commodity based on the number of each commodity in the N to-be-processed orders, wherein the number of each commodity in the at least one commodity is larger than the number of each remaining commodity in the N to-be-processed orders; and

The target commodity is added to the initial target set.

11. A wave order set creation apparatus, comprising:

the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module acquires a plurality of to-be-processed orders, and each to-be-processed order in the plurality of to-be-processed orders comprises at least one commodity;

the creating module is used for creating a wave order set based on the commodity similarity among the plurality of to-be-processed orders, wherein the commodity similarity among the to-be-processed orders in the wave order set meets a preset similarity condition;

the first processing module is used for processing the wave order set to obtain summarized information, wherein the summarized information comprises commodity categories in the wave order set and commodity quantity corresponding to the commodity categories; and

the first determining module is used for determining target storage positions of commodities in the wave order set based on the summarized information, and positioning the commodities in the wave order set at the same or adjacent storage positions so as to acquire the commodities in the wave order set from the target storage positions;

12. A computing device, 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 method of any of claims 1 to 10.

13. A computer readable storage medium storing computer executable instructions which when executed are adapted to implement the method of any one of claims 1 to 10.