CN111523977A

CN111523977A - Wave order set creating method and device, computing equipment and medium

Info

Publication number: CN111523977A
Application number: CN202010329684.5A
Authority: CN
Inventors: 许群合
Original assignee: Beijing Jingdong Shangke Information Technology Co Ltd
Current assignee: Beijing Jingdong Shangke Information Technology Co Ltd
Priority date: 2020-04-23
Filing date: 2020-04-23
Publication date: 2020-08-11
Anticipated expiration: 2040-04-23
Also published as: CN111523977B

Abstract

The present disclosure provides a method for creating a wave order set, executed by a computing device, the method comprising: the method comprises the steps of obtaining a plurality of orders to be processed, wherein each order to be processed in the plurality of orders to be processed comprises at least one commodity; creating a wave order set based on commodity similarity among a plurality of orders to be processed, wherein the commodity similarity among the orders to be processed in the wave order set meets a preset similar condition; processing the wave order set to obtain summary information, wherein the summary information comprises commodity types in the wave order set and commodity quantity corresponding to the commodity types; and determining a target storage position of the goods in the wave order set based on the summary information so as to obtain the goods in the wave order set from the target storage position. The disclosure also provides a device for creating the wave order set, a computing device and a computer readable storage medium.

Description

Wave order set creating method and device, computing equipment and medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a method for creating a wayside order set, an apparatus for creating a wayside order set, a computing device, and a computer-readable storage medium.

Background

In many warehousing operations, picking of goods is usually performed according to orders. However, the related art item picking process is to perform picking operations on an order-by-order basis.

In the process of implementing the present disclosure, the inventor finds that in the related art, in the warehousing operation of the related art, the goods picking process is basically performed by positioning, picking operation, and the like according to one order, so that a plurality of orders similar to the goods can be picked at one storage location, but since the positioning is performed a plurality of times one order is performed, a plurality of picking operations are required for a plurality of orders similar to the goods, so that the picking efficiency is low.

Disclosure of Invention

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

One aspect of the present disclosure provides a method of creating a wave order set, performed by a computing device, the method comprising: the method comprises the steps of obtaining a plurality of orders to be processed, wherein each order to be processed in the plurality of orders to be processed comprises at least one commodity, creating a wave order set based on commodity similarity among the plurality of orders to be processed, processing the wave order set to obtain summary information, wherein the summary information comprises commodity categories in the wave order set and commodity numbers corresponding to the commodity categories, and determining target storage positions of the commodities in the wave order set based on the summary information so as to obtain the commodities in the wave order set from the target storage positions.

According to an embodiment of the present disclosure, the step of satisfying the preset similarity condition for the commodity similarity between the orders to be processed in the wayside order set includes: each order to be processed in the wave order set is provided with commodities of a preset category, and the ratio of the category quantity of the preset category to the category quantity of each order to be processed meets a 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 the creating a wave order set based on commodity similarity between the plurality of orders to be processed comprises: 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, and determining M to-be-processed orders in the N to-be-processed orders as the wave order set based on a first overlap ratio of each to-be-processed order in the N to-be-processed orders and the initial target set, wherein the first overlap ratio is used for representing the similarity degree of the 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.

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

According to an embodiment of the present disclosure, the determining M to-be-processed orders of the N to-be-processed orders based on a first overlap ratio between each of the N to-be-processed orders and the initial target set further includes performing in a loop when a preset condition is satisfied: calculating a second overlap ratio of the to-be-processed orders which are not added to the current target set in the N to-be-processed orders and the current target set, sequentially adding the to-be-processed orders which are not added to the current target set according to a descending order of the second overlap ratio, and updating the current target set when the second overlap ratio is smaller than a preset threshold value, wherein the to-be-processed orders in the current target set after execution are determined as the M to-be-processed orders.

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

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

According to an embodiment of the present disclosure, the first overlap ratio includes a ratio between a number of a first product intersection and a number of products of each of the N to-be-processed orders, where the first product intersection is an intersection between a product of each of the N to-be-processed orders and a product in the initial target set, and the second overlap ratio includes a ratio between a number of a second product intersection and a number of products of each to-be-processed order that has not yet been added to the current target set, where the second product intersection is an intersection between a product of each to-be-processed order that has not yet been added to the current target set and a product in the current target set.

According to an embodiment of the present disclosure, the method further includes: processing the orders to be processed in the wave order set to obtain K types of commodities and the quantity of each type of commodity 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 types of commodities based on the K types of commodities and the quantity of each type of commodity in the K types of commodities, and generating a positioning result of each order to be processed in the wave order set based on the at least one storage position, wherein the positioning result of each order to be processed comprises the storage position and the quantity of the commodities in the order.

According to an embodiment of the present disclosure, the method further includes: determining a plurality of orders to be processed with consistent storage positions and a sum of the quantities of the commodities as a preset quantity as a spliced order based on the positioning result of each order to be processed in the order collection, wherein the preset quantity represents the quantity of the commodities stored in the storage unit, generating at least one picking task based on the spliced order, wherein a plurality of orders to be processed belonging to the same spliced order belong to one picking task of the at least one picking task, and generating a picking collection sheet based on the at least one picking task so as to execute the picking tasks to corresponding storage positions based on the picking collection sheet.

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

Another aspect of the present disclosure provides an apparatus for creating 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 orders to be processed, wherein each order to be processed in the plurality of orders to be processed comprises at least one commodity. The creating module is used for creating a wave order set based on commodity similarity among the multiple orders to be processed, wherein the commodity similarity among the orders to be processed in the wave order set meets a preset similar condition. And the first processing module is used for processing the wave order set to obtain summary information, wherein the summary information comprises the commodity types in the wave order set and the commodity quantity corresponding to the commodity types. And the first determining module is used for determining a target storage position of the commodities in the wave order set based on the summary information so as to obtain the commodities in the wave order set from the target storage position.

According to the embodiment of the present disclosure, the 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 orders to be processed in the order set of the times to obtain K types of commodities and the number of each type of commodity in the K types of commodities, wherein K is an integer greater than or equal to 1. The second determining module determines 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. And the first generation module is used for 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 and the quantity of the commodities in the order.

According to the embodiment of the present disclosure, the apparatus further includes: the device comprises a third determining module, a second generating module and a third generating module. The third determining module determines a plurality of to-be-processed orders with consistent storage positions and a sum of the quantities of commodities being a preset quantity as a spliced order based on a positioning result of each to-be-processed order in the wave order set, wherein the preset quantity represents the quantity of commodities stored in the storage unit. And the second generation module generates at least one picking task based on the spliced orders, wherein a 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 the third generation module generates the order picking collection sheet based on the at least one order picking task so as to execute the order picking task to the corresponding storage position based on the order picking collection sheet.

Another aspect of the present disclosure provides a computer-readable storage medium storing computer-executable instructions for implementing the method as described above when executed.

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

According to the embodiment of the disclosure, the problem that in the related art, the goods picking process is basically to perform positioning, picking operation and the like according to one order, so that a plurality of orders similar to the goods can be picked in one storage position, but the similar orders need to be picked for a plurality of times due to the fact that the orders are positioned for a plurality of times one by one, so that the picking efficiency is low can be solved, 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 of the present disclosure with reference to the accompanying drawings, in which:

fig. 1 schematically shows a system architecture of a method and an apparatus for creating a wave order set according to an embodiment of the present disclosure;

FIG. 2 schematically illustrates a flow chart of a method of creating a wave order set according to an embodiment of the disclosure;

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

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

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

FIG. 6 schematically illustrates a block diagram of a computer system suitable for the creation of a wave order set according to an embodiment of the 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.).

An embodiment of the present disclosure provides a method for creating a wayside order set, which is executed by a computing device, and includes: the method comprises the steps of obtaining a plurality of orders to be processed, wherein each order to be processed in the plurality of orders to be processed comprises at least one commodity, creating a wave order set based on commodity similarity among the plurality of orders to be processed, wherein the commodity similarity among the orders to be processed in the wave order set meets a preset similarity condition, processing the wave order set to obtain summary information, wherein the summary information comprises commodity categories in the wave order set and commodity numbers corresponding to the commodity categories, and determining target storage positions of the commodities in the wave order set based on the summary information so as to obtain the commodities in the wave order set from the target storage positions.

Fig. 1 schematically shows a system architecture of a method and an apparatus for creating a wayside 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 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, wireless communication links, or fiber optic cables, to name a few.

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 shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, 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 method for creating a wave order set provided by the embodiment of the present disclosure may be generally executed by the server 105. Accordingly, the creating device of the wayside order set provided by the embodiment of the present disclosure can be generally disposed in the server 105. The method for creating the wayside order set provided by the embodiment of the present disclosure may also be executed by a server or a 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. Accordingly, the creating apparatus for the wayside order set provided by the embodiment of the present disclosure may also be disposed in a server or a server cluster that is different from the server 105 and can communicate with the

terminal devices

101, 102, 103 and/or the server 105.

For example, the multiple to-be-processed orders of the embodiment of the present disclosure may be stored in the

terminal devices

101, 102, and 103, and the multiple to-be-processed orders are sent to the server 105 through the

terminal devices

101, 102, and 103, and the server 105 may create the wave order set based on the commodity similarity between the multiple to-be-processed orders, or the

terminal devices

101, 102, and 103 may also create the wave order set directly based on the commodity similarity between the multiple to-be-processed orders. In addition, the plurality of orders to be processed may also be directly stored in the server 105, and the wave order set is created by the server 105 directly based on the commodity similarity between the plurality of orders to be processed.

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 shows a flowchart of a method of creating a wave order set according to an embodiment of the present disclosure.

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

In operation S210, a plurality of pending orders are obtained, wherein each pending order of the plurality of pending orders includes at least one item.

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

In operation S220, a wayside order set is created based on commodity similarity between a plurality of to-be-processed orders, where the commodity similarity between the to-be-processed orders in the wayside order set satisfies a preset similarity condition.

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

For example, the preset categories include a categories, and taking one to-be-processed order as an example, the categories of the commodities in the to-be-processed order are b categories, where a ratio between a and b is greater than a preset ratio, for example. The preset ratio includes, for example, a preset threshold, that is, the value of a/b is greater than, for example, the preset threshold.

In the embodiment of the present disclosure, in order to improve the sorting efficiency, the to-be-processed orders with higher product similarity among the multiple to-be-processed orders are created into the order set with higher similarity, so that the order set with higher product similarity among the to-be-processed orders is realized, and when sorting is performed on the order set with higher similarity, all the products in the to-be-processed orders in the order set with higher similarity can be obtained by obtaining the products with fewer product classes.

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

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

According to the embodiment of the disclosure, the commodities in the order collection of the times can be located to obtain the target storage position based on the summary information, so that picking is carried out based on the target storage position. The goods in the wave order set can be positioned at the same or adjacent storage positions as much as possible, and the unpacking of containers at different storage positions in the warehouse is reduced, namely, the located goods in each container are ensured to be used as the goods in one wave order set as much as possible.

It can be understood that the wayside order set is created based on the similarity of the commodities among the orders to be processed, so that the order picking is carried out based on the wayside order set, and the order picking efficiency is improved. In addition, the wave order set is summarized to obtain summary information, positioning is carried out on the basis of the summary information to obtain a positioning result, and goods picking is carried out on the basis of the positioning result, so that the unpacking times are reduced.

According to the embodiment of the present disclosure, the creating of the wave order set in operation S220 described above may include the following steps (1) to (2), for example, with respect to the product similarity between the plurality of orders to be processed.

(1) According to the embodiment of the disclosure, the plurality of orders to be processed includes, for example, N orders to be processed, 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 present disclosure, each of the N pending orders includes at least one commodity, and therefore, the N pending orders include a plurality of commodities. The target article may be, for example, at least one of a plurality of articles. For example, the target item may be one or more items of the plurality of items having the greatest number.

After the target item is determined, the target item may be added to the initial target set. Before adding the target item to the initial target set, the initial target set is, for example, an empty set, i.e., the empty set may not include any item.

According to an embodiment of the present disclosure, processing N to-be-processed orders to obtain an initial target set specifically includes: the quantity 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 to be used as a target commodity based on the quantity of each commodity in the N orders to be processed. The quantity of each commodity in the at least one commodity is larger than the quantity of each remaining commodity in the N orders to be processed. Namely, one or more commodities with the most data in the N orders to be processed are determined as target commodities. For example, all the commodities in the N orders to be processed are arranged from large to small in number, and one or more commodities arranged in front are determined as target commodities. The target good is then added to the initial target set.

In the embodiment of the present disclosure, other commodities whose storage locations are close to the target commodity may also be added to the initial target set. The other goods may be, for example, goods in the N pending orders, or goods other than the N pending orders. It is understood that the storage position of the other commodity is close to the target commodity, which can indicate that the similarity between the other commodity and the target commodity is higher. That is, the other product and the target product may be the same type of product. The storage location may be, for example, a logical area, a lane, a storage area, a storage location, etc. in a warehouse.

(2) Determining M to-be-processed orders in the N to-be-processed orders as a wave order set based on a first overlap ratio of each to-be-processed order in the N to-be-processed orders and the initial target set, wherein the first overlap 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 to-be-processed order in the N to-be-processed orders may be respectively compared with the initial target set to obtain orders in which the commodities in the N to-be-processed orders are similar to the commodities in the initial target set. For example, orders of the N pending orders that are similar to the initial target set are determined by calculating a first degree of overlap of each pending order with the initial target set. Wherein a higher first degree of overlap indicates a higher similarity of the pending order to the initial target set. In the implementation of the present disclosure, by calculating the first contact ratio, M to-be-processed orders can be determined from the N to-be-processed orders as a wave order set, so as to process orders in the wave order set in a centralized manner. That is, the M pending orders within the one wave order set 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, the determining the target storage location of the product in the wave order set based on the summary information in operation S240 may include: and determining target storage positions of the commodities with the M orders to be processed so as to obtain the commodities with the M orders to be processed from the target storage positions. For example, embodiments of the present disclosure may aggregate the target storage location for each item in the M pending orders within the wave order set to take the target storage location as a pick destination.

According to the embodiment of the disclosure, the similarity of the commodities in the M pending orders in one wave order set is high, for example, and therefore the target storage locations of the commodities in the M pending orders are closer, for example. Therefore, the order in one wave order set is processed in a centralized mode, the picking efficiency can be improved, namely all the commodities in the M orders to be processed can be obtained 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, and order 4. The order 1 includes, for example, a product a, a product B, and a product C. Order 2 includes, for example, item D. The order 3 includes, for example, article a and article B. Order 4 includes, for example, item E. For example, if the storage locations of the items a to E are different, the order 1, the order 2, the order 3, and the order 4 are sequentially picked. Then for example 3 storage locations need to be picked for order 1, 1 storage location for order 2, 2 storage locations for order 3, and 1 storage location for order 4. And since multiple orders are picked in turn, the same items in order 1 and order 3 need to be picked repeatedly. In addition, the storage positions of the picked goods for the same goods at each time may be different, so that the containers need to be disassembled for multiple times, and the situation that the goods of the containers are disassembled to be zero cannot be avoided. For example, if each bin has 10 items a, if order 1 includes 4 items a and order 3 includes 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 zeroed out and the zeroed bins not being conveniently stored.

Through the technical scheme of the embodiment of the disclosure, a plurality of similar orders are used as a once order set, and the orders in the once order set are processed in a centralized manner, so that the picking effect can be at least improved, and the effect of removing zero parts from the container is reduced. Through a specific process as described in fig. 3.

Fig. 3 schematically illustrates a flow chart of a method of creating a wave order set 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 again here.

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

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

In operation S330, a location result of each to-be-processed order in the wave order set is generated based on the at least one storage location, where the location result of each to-be-processed order includes a storage location of the item in the order.

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

For example, as exemplified above, the example continues with the N pending orders including order 1, order 2, order 3, and order 4. For example, order 1 and order 3 are determined to be similar M pending orders. The order 1 and order 3 are for example as a wave order set. The order 1 includes, for example, a product a, a product B, and a product C. The order 3 includes, for example, article a and article B.

Then, the order 1 and the order 3 are processed, and the obtained K-class commodities include, for example, commodity a class, commodity B class, and commodity C class. Then, the number of items corresponding to each of the item a class, item B class, and item C class is determined, for example, the number of items corresponding to the item a class is 10 (order 1 has 4 items a, and order 3 has 6 items a). The category of products B is similar to the category of products C, and will not be described herein. For ease of understanding, the number of products corresponding to the product category a is 10 in the following example. After determining the quantity of the commodities corresponding to each type of commodities, the storage position of each type of commodities can be further determined. For example, after determining that the number of the commodities corresponding to the commodity a class is 10, it is further determined that the storage location of the commodity a is the container 1, and the container 1 includes, for example, 10 commodities a. Then, 10 items a in the container 1 can be identified as items of item class a in the wave order set. For example, the positioning result for order 1 includes 4 items a in container 1, and the positioning result for order 3 includes 6 items a in container 1. It can be appreciated that the embodiments of the present disclosure summarize the quantity of commodities for K categories in a wave order set, and then locate the storage locations of the commodities in the K categories based on the summarized result, and assign the storage locations to each order in the wave order set.

It can be understood that according to the technical scheme of the embodiment of the disclosure, similar orders are determined to be a wave order set, and the item category collection, the positioning and the positioning result distribution are performed on each order in the wave order set in a wave order set, so that the picking efficiency is greatly improved, and the container zero removal is reduced.

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

and determining a plurality of to-be-processed orders with consistent storage positions and the sum of the quantity of commodities being a preset quantity as a splicing order based on the positioning result of each to-be-processed order in the wave order set, wherein the preset quantity represents the quantity of commodities stored in the storage unit.

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

And generating at least one picking task based on the combined order, wherein a plurality of to-be-processed orders belonging to the same combined order belong to one picking task in the at least one picking task. For example, a plurality of pending orders within a stitched order are a picking task, e.g., order 1 and order 3 are a picking task.

Based on the at least one picking task, a picking order is generated to facilitate execution of the picking task to the corresponding storage location based on the picking order. For example, a plurality of picking tasks based on the order collection can be gathered to obtain a picking collection list, and when picking is carried out based on the picking collection list, picking can be carried out on each picking task, so that the picking efficiency is greatly improved, and the container zero removal is reduced.

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

According to the embodiment of the present disclosure, determining M of the N to-be-processed orders as a wave order set based on a first degree of overlap of each of the N to-be-processed orders with the initial target set, for example, includes the following processes.

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

For example, consider a current pending order of N pending orders. The number of items currently pending is, for example, n, and the number of items in the initial target set is, for example, c, then the number of intersection of the first items is (n # c). The first contact ratio C between the current pending order and the initial target set is, for example:

if the first contact ratio C is 1, all the commodities in the current order to be processed are in the initial target set. If the first contact ratio C is less than 1, the partial goods in the current pending order are not in the initial target set.

And then, sequentially adding the N orders to be processed to the initial target set according to the sequence of the first contact ratio from large to small 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 the embodiment of the present disclosure, the first contact ratio being less 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 are illustrated as including order 1, order 2, order 3, order 4, and so on. Order 1 includes, for example, item a. The order 2 includes, for example, article B and article C. The order 3 includes, for example, the product C and the product D. Order 4 includes, for example, item E. The initial target set includes, for example, article a and article B.

Then, first contact ratios of the order 1, the order 2, the order 3 and the order 4 are sequentially calculated, and the obtained first contact ratios of the order 1, the order 2, the order 3 and the order 4 are 1, 0.5, 0 and 0 respectively. And adding the order 1, the order 2, the order 3 and the order 4 to the initial target set from large to small according to the first contact ratio. For example, after adding order 1 and order 2 into the initial target set in sequence, the adding is stopped, because the first degree of overlap of the last added order 2 is smaller than the preset threshold. It will be appreciated that the resulting current set of targets includes, for example, order 1 and order 2. That is, the current target set includes, for example, article a, article B, and article C.

Then, the following steps (1) to (3) are cyclically executed under the condition that a preset condition is satisfied. The meeting of the preset condition includes, for example: the number of commodities in the current target set is smaller than the preset number of the targets, or the N orders to be processed are not added to the current target set. That is, the embodiment of the present disclosure may execute the following steps (1) to (3) in a loop 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 been completely added to the current target set.

(1) And calculating a second overlapping degree 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 intersections of the second item and the number of items of each pending order that have not yet been added to the current target set. And the second commodity intersection is the intersection of the commodity of each to-be-processed order which is not added to the current target set and the commodity in the current target set. The calculation process of the second overlap ratio is, for example, the same as or similar to the calculation process of the first overlap ratio, and is not described herein again.

For example, the pending orders of the N pending orders that have not been added to the current target set include, for example, order 3 and order 4. The order 3 includes, for example, the product C and the product D. Order 4 includes, for example, item E. The current target set includes, for example, article a, article B, and article C. The second overlap ratios of order 3 and order 4 are calculated, respectively, resulting in a second overlap ratio of order 3 and order 4 of, for example, 0.5, 0, respectively.

(2) And adding the orders to be processed which are not added to the current target set in sequence according to the sequence from the second overlap ratio from large to small. For example, order 3 is added to the current target set.

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

Since the second degree of overlap for order 3 is less than 1, after order 3 is added to the current target set, no further orders (e.g., order 4) are 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 article a, article B, article C, and article D.

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

And if the quantity of the commodities in the current target set is larger than or equal to the preset quantity of the targets, stopping continuously 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. And if the N orders to be processed have the remaining orders which are not added to the current target set, continuing to process the remaining orders to generate a new wave order set. The processing manner for continuously processing the remaining orders is the same as or similar to the processing manner for obtaining the M orders to be processed, and is not described herein again.

It will be appreciated that after each addition of a new order to either the initial target set or the current target set, supplemental items similar to the new order just added may be added to the current target set to update the current target set in real-time.

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

It will be appreciated that embodiments of the present disclosure determine a wave order set comprising a plurality of orders by determining a degree of overlap of the pending order with the initial target set or the current target set. The commodity contact ratio among the orders in each wave order set is high, namely the orders in each wave order set are similar. Because a plurality of orders in each wave order set are similar, the commodity types in each wave order set are fewer, and the quantity of commodities corresponding to each commodity type is larger, so that the picking efficiency is improved, and the container zero removal is reduced. For example, because the similarity of the goods in each wave order set is high, when one wave order set is processed, fewer storage positions can be located, and the locating efficiency is improved. The picking path is shorter by positioning less storage positions, so that the picking time is shortened, the picking times are reduced, and the effect of improving the picking efficiency is achieved.

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

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

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

The creating module 420 may be configured to create a running order set based on commodity similarity between a plurality of orders to be processed, where the commodity similarity between the orders to be processed in the running order set satisfies a preset similarity condition. According to the embodiment of the present disclosure, the creating module 420 may perform, for example, the operation S220 described above with reference to fig. 2, which is not described herein again.

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

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

Fig. 5 schematically shows a block diagram of a device for creating a wave order set according to another embodiment of the present disclosure.

As shown in fig. 5, the apparatus 500 for creating a wave order set includes, for example, an obtaining 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 again.

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

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

The first generating module 530 may be configured to generate a location result of each to-be-processed order in the order set based on the at least one storage location, where the location result of each to-be-processed order includes a storage location and a quantity of the item in the order. According to the embodiment of the present disclosure, the first generating module 530 may perform, for example, the operation S330 described above with reference to fig. 3, which is not described herein again.

According to the embodiment of the disclosure, the commodity similarity meeting the preset similarity condition between the orders to be processed in the wave order set comprises: each order to be processed in the wave order set has commodities of a preset category, and the ratio between the category quantity of the preset category and the category quantity of each order to be processed meets a preset ratio.

According to the embodiment of the disclosure, the plurality of to-be-processed orders includes N to-be-processed orders, where N is an integer greater than or equal to 1. Wherein creating a wave order set based on commodity similarities between the plurality of orders to be processed 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, determining M orders to be processed in the N orders to be processed as a wave order set based on a first overlap ratio of each order to be processed in the N orders to be processed and the initial target set, the first overlap ratio is used for representing the similarity degree of the commodities of each order to be processed and 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 of the N pending orders based on a first degree of overlap of each of the N pending orders with the initial target set includes: calculating a first contact ratio of each to-be-processed order in the N to-be-processed orders and the initial target set, sequentially adding the N to-be-processed orders to the initial target set according to the sequence of the first contact ratios from large to small to obtain a current target set until the first contact ratio of the currently-added to-be-processed order is smaller than a preset threshold value, wherein the to-be-processed order added to the initial target set is 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 further includes performing in a loop when a preset condition is satisfied, based on a first overlap ratio of each pending order of the N pending orders with the initial target set: calculating a second overlap ratio of the to-be-processed orders which are not added to the current target set in the N to-be-processed orders and the current target set, sequentially adding the to-be-processed orders which are not added to the current target set according to the sequence from the second overlap ratio from large to small, updating the current target set when the second overlap ratio is smaller than a preset threshold value, and determining the to-be-processed orders in the current target set after execution is M to-be-processed orders.

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

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

According to the embodiment of the present disclosure, the first coincidence degree includes a ratio between the number of first product intersections and the number of products of each of the N to-be-processed orders, where the first product intersection is an intersection between a product of each of the N to-be-processed orders and a product in the initial target set, and the second coincidence degree includes a ratio between the number of second product intersections and the number of products of each to-be-processed order that has not been added to the current target set, where the second product intersection is an intersection between a product of each to-be-processed order that has not been added to the current target set and a product in the current target set.

According to an embodiment of the present disclosure, the

apparatus

400 or 500 may further include: the device comprises a third determining module, a second generating module and a third generating module. The third determining module determines a plurality of to-be-processed orders with consistent storage positions and preset number of sum of the number of commodities as a splicing order based on the positioning result of each to-be-processed order in the wave order set, wherein the preset number represents the number of commodities stored in the storage unit. And the second generation module generates at least one picking task based on the spliced orders, wherein a 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 the third generation module generates the order picking collection sheet based on at least one order picking task so as to execute the order picking task to the corresponding storage position based on the order picking collection sheet.

According to an embodiment of the present disclosure, processing N to-be-processed orders to obtain an initial target set includes: 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 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 obtaining module 410, the creating module 420, the first processing module 430, the first determining module 440, the second processing module 510, the second determining module 520, and the first generating module 530 may be combined into one module to be implemented, or any one of them may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the disclosure, at least one of the obtaining module 410, the creating module 420, the first processing module 430, the first determining module 440, the second processing module 510, the second determining module 520, and the first generating module 530 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 hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or in any one of three implementations of software, hardware, and firmware, or in any suitable combination of any of them. Alternatively, at least one of the obtaining module 410, the creating module 420, the first processing module 430, the first determining module 440, the second processing module 510, the second determining module 520 and the first generating module 530 may be at least partially implemented as a computer program module, which when executed, may perform a corresponding function.

FIG. 6 schematically illustrates a block diagram of a computer system suitable for the creation of a wave order set according to an embodiment of the disclosure. The computer system illustrated in FIG. 6 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. 6, a computer system 600 according to an embodiment of the present disclosure includes a processor 601 which 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. Processor 601 may include, 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 601 may also include onboard memory for caching purposes. Processor 601 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 603, various programs and data necessary for the operation of the system 600 are stored. The processor 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. The processor 601 performs various operations of the method flows according to the embodiments of the present disclosure by executing programs in the ROM 602 and/or RAM 603. It is to be noted that the programs may also be stored in one or more memories other than the ROM 602 and RAM 603. The processor 601 may also perform various operations of the 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 600 may also include an input/output (I/O) interface 605, input/output (I/O) interface 605 also connected to 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, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; 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 driver 610 is also connected to the I/O interface 605 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted in the storage section 608 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 609, and/or installed from the removable medium 611. The computer program, when executed by the processor 601, 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 storage 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, the computer-readable storage medium may be a computer-non-volatile computer-readable storage medium, which may include, for example and without limitation: 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 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.

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

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

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

the method comprises the steps of obtaining a plurality of orders to be processed, wherein each order to be processed in the plurality of orders to be processed comprises at least one commodity;

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

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

and determining a target storage position of the goods in the wave order set based on the summary information so as to obtain the goods in the wave order set from the target storage position.

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

each order to be processed in the wave order set is provided with commodities of a preset category, and the ratio of the category quantity of the preset category to the category quantity of each order to be processed meets a preset ratio.

3. The method of claim 1, wherein the plurality of pending orders comprises N pending orders, N being an integer greater than or equal to 1;

wherein the creating a wave order set based on commodity similarity between the plurality of orders to be processed 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; and

determining M to-be-processed orders in the N to-be-processed orders as the wave order set based on a first overlap ratio of each to-be-processed order in the N to-be-processed orders and the initial target set, wherein the first overlap 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.

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

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

sequentially adding N orders to be processed to the initial target set according to the sequence of the first contact ratio from large to small 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.

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

calculating a second overlap ratio between the current target set and the pending orders not yet added to the current target set among the N pending orders;

adding orders to be processed which are not added to the current target set in sequence according to the sequence of the second overlap ratio from large to small; and

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

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

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

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

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

7. The method of claim 5, wherein the updating the current target set comprises:

determining supplementary commodities with the similarity meeting the preset similarity with the commodities in the current target set; and

adding the supplemental merchandise to the current target set,

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

8. The method of claim 5, wherein:

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

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

9. The method of claim 1, further comprising:

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

determining at least one storage location of the K-class commodities based on the K-class commodities and the number of each of the K-class commodities; 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 and the quantity of the commodities in the order.

10. The method of claim 9, further comprising:

determining a plurality of to-be-processed orders with consistent storage positions and a sum of the quantities of commodities being a preset quantity as a spliced order based on a positioning result of each to-be-processed order in the wave order set, wherein the preset quantity represents the quantity of commodities stored in a storage unit;

generating at least one picking task based on the combined order, wherein a plurality of to-be-processed orders belonging to the same combined order belong to one picking task in the at least one picking task; and

based on the at least one picking task, a picking order is generated to facilitate execution of picking tasks to corresponding storage locations based on the picking order.

11. The method of claim 2, wherein said processing said N pending orders resulting in 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 orders to be processed as the target commodity based on the quantity of each commodity in the N orders to be processed, wherein the quantity of each commodity in the at least one commodity is greater than the quantity of each remaining commodity in the N orders to be processed; and

adding the target item to the initial target set.

12. An apparatus for creating a wave order set, comprising:

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

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

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

and the first determining module is used for determining a target storage position of the commodities in the wave order set based on the summary information so as to obtain the commodities in the wave order set from the target storage position.

13. 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 1-11.

14. A computer-readable storage medium storing computer-executable instructions for implementing the method of any one of claims 1 to 11 when executed.