CN113019959A

CN113019959A - Article sorting method, apparatus, electronic device and computer readable medium

Info

Publication number: CN113019959A
Application number: CN202110581825.7A
Authority: CN
Inventors: 邓博洋; 程杨武
Original assignee: Beijing Missfresh Ecommerce Co Ltd
Current assignee: Shenzhen Zhuanxin Intellectual Property Service Co.,Ltd.
Priority date: 2021-05-27
Filing date: 2021-05-27
Publication date: 2021-06-25
Anticipated expiration: 2041-05-27
Also published as: CN113019959B

Abstract

The embodiment of the disclosure discloses an article sorting method, an article sorting device, electronic equipment and a computer readable medium. One embodiment of the method comprises: acquiring an order information set; generating total volume of the articles based on article quantity groups and article volume groups included in each order information in the order information set to obtain a total article volume set; selecting basket information corresponding to the total volume of each article in the article total volume set as target basket information to obtain a target basket information set; for each order information in the order information set, obtaining shelf information corresponding to each item name in an item name group included in the order information to obtain a shelf information group; and combining each order information in the order information set, the target basket information corresponding to the order information and the goods shelf information group to generate order sorting information to obtain an order sorting information set. This embodiment has improved the efficiency of goods letter sorting, has saved the time of choosing goods.

Description

Article sorting method, apparatus, electronic device and computer readable medium

Technical Field

Embodiments of the present disclosure relate to the field of computer technologies, and in particular, to an article sorting method, an apparatus, an electronic device, and a computer-readable medium.

Background

With the development of internet technology, online shopping gradually goes deep into the lives of people. The advantages of online shopping (e.g., convenience, quickness, variety, etc.) are of great appeal and impact to users, with more and more people selecting online shopping. Currently, when a conventional logistics supplier performs logistics delivery, the general picking method is as follows: the picker holds the PDA by hand to search for the goods corresponding to the user order, then puts the goods on the trolley, packages the goods in a unified way, and transports the goods to a transport vehicle for distribution.

However, the above-mentioned picking method usually has the following technical problems:

firstly, goods corresponding to the user orders need to be manually searched from the goods shelf for multiple times, so that the goods sorting efficiency is low, and a large amount of goods sorting time is consumed;

secondly, different types of articles are not classified and packaged, so that when some articles (such as beverage wine) are damaged, the loss of other articles is high;

third, the transport vehicles are not properly selected, which may require repeated scheduling of vehicles for transport, resulting in waste of transport resources.

Disclosure of Invention

This summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter.

Some embodiments of the present disclosure propose an item sorting method, apparatus, electronic device and computer readable medium to solve one or more of the technical problems mentioned in the background section above.

In a first aspect, some embodiments of the present disclosure provide a method of sorting articles, the method comprising: obtaining order information submitted by each user in a user group to obtain an order information set, wherein the order information in the order information set comprises: the system comprises an article name group, an article quantity group and an article volume group, wherein the article name in the article name group corresponds to the article quantity in the article quantity group, and the article name in the article name group corresponds to the article volume in the article volume group; generating total volume of the articles based on the article quantity group and the article volume group included in each order information in the order information set to obtain a total article volume set; selecting basket information corresponding to the total volume of each article in the total volume of articles set as target basket information based on a preset basket information set to obtain a target basket information set, wherein the basket information in the basket information set comprises a basket number and a basket volume; for each order information in the order information set, executing the following processing steps: acquiring shelf information corresponding to each item name in an item name group included in the order information to obtain a shelf information group, wherein the shelf information in the shelf information group includes shelf identification; and combining each order information in the order information set, the target basket information corresponding to the order information and the goods shelf information group to generate order sorting information to obtain an order sorting information set.

In a second aspect, some embodiments of the present disclosure provide an article sorting apparatus comprising: the first obtaining unit is configured to obtain order information submitted by each user in a user group, and obtain an order information set, where the order information in the order information set includes: the system comprises an article name group, an article quantity group and an article volume group, wherein the article name in the article name group corresponds to the article quantity in the article quantity group, and the article name in the article name group corresponds to the article volume in the article volume group; the generating unit is configured to generate total volume of the articles based on the article quantity group and the article volume group included in each order information in the order information set, so as to obtain an article total volume set; the selection unit is configured to select basket information corresponding to the total volume of each article in the total volume of articles as target basket information based on a preset basket information set to obtain a target basket information set, wherein the basket information in the basket information set comprises a basket number and a basket volume; a second obtaining unit configured to perform, for each order information in the order information set, the following processing steps: acquiring shelf information corresponding to each item name in an item name group included in the order information to obtain a shelf information group, wherein the shelf information in the shelf information group includes shelf identification; and the combining unit is configured to combine each order information in the order information set, the target basket information corresponding to the order information and the shelf information group to generate order sorting information, so as to obtain an order sorting information set.

In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon, which when executed by one or more processors, cause the one or more processors to implement the method described in any of the implementations of the first aspect.

In a fourth aspect, some embodiments of the present disclosure provide a computer readable medium on which a computer program is stored, wherein the program, when executed by a processor, implements the method described in any of the implementations of the first aspect.

The above embodiments of the present disclosure have the following advantages: by the article sorting method according to some embodiments of the disclosure, the situation that the goods corresponding to the user orders are manually searched from the goods shelf for many times is avoided, the goods sorting efficiency is improved, and the goods sorting time is saved. In particular, the reason why a large amount of picking time is consumed is that: goods corresponding to the user orders need to be manually searched from the goods shelf for many times, so that the goods sorting efficiency is low, and a large amount of goods sorting time is consumed. Based on this, in the article sorting method according to some embodiments of the present disclosure, first, order information submitted by each user in the user group is obtained, and an order information set is obtained. Therefore, the goods baskets and the corresponding goods shelves can be conveniently screened subsequently according to the order information. And secondly, generating the total volume of the articles based on the article quantity group and the article volume group included in each order information in the order information set to obtain the total article volume set. Therefore, data support is provided for subsequently screening reasonable goods baskets. And then, based on a preset basket information set, selecting basket information corresponding to the total volume of each article in the total volume of articles set as target basket information to obtain a target basket information set. Therefore, reasonable goods baskets can be screened out to bear various articles corresponding to the order information sets. Then, for each order information in the order information set, the following processing steps are performed: and obtaining shelf information corresponding to each item name in the item name group included in the order information to obtain a shelf information group. Therefore, the shelf information of the goods represented by the name of each goods included in each order information in the order information set can be determined, and the situation that the goods corresponding to the user order are found from the shelf many times manually is avoided. And finally, combining each order information in the order information set, the target basket information corresponding to the order information and the goods shelf information group to generate order sorting information to obtain an order sorting information set. Therefore, the basket information and the shelf information group corresponding to each order information in the order information set can be determined, and the sorting processing is facilitated. Therefore, the goods corresponding to the user orders are prevented from being manually searched from the goods shelf for many times, the goods sorting efficiency is improved, and the goods sorting time is saved.

Drawings

The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. Throughout the drawings, the same or similar reference numbers refer to the same or similar elements. It should be understood that the drawings are schematic and that elements and elements are not necessarily drawn to scale.

1-2 are schematic diagrams of one application scenario of an item sorting method according to some embodiments of the present disclosure;

fig. 3 is a flow chart of some embodiments of an article sorting method according to the present disclosure;

FIG. 4 is a flow chart of still further embodiments of a method of sorting articles according to the present disclosure;

fig. 5 is a schematic structural view of some embodiments of an article sorting apparatus according to the present disclosure;

FIG. 6 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.

It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.

It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.

It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.

The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Fig. 1 is a schematic diagram of an application scenario of an item sorting method according to some embodiments of the present disclosure.

In the application scenario of fig. 1, first, the computing device 101 may obtain order information submitted by each user in the user group, resulting in an order information set 102. The order information in the order information set 102 includes: an item name group, an item quantity group, and an item volume group. The item names in the item name group correspond to the item quantities in the item quantity group. The item names in the item name group correspond to the item volumes in the item volume group. Next, the computing device 101 may generate a total volume of the items based on the quantity group and the volume group of the items included in each order information in the order information set 102, so as to obtain an overall item volume set 103. Next, the computing device 101 may select, based on a preset basket information set 104, basket information corresponding to the total volume of each article in the above-described total article volume 103 as target basket information, resulting in a target basket information set 105. The basket information in the basket information set 104 includes a basket number and a basket volume. Then, the computing device 101 may perform the following processing steps for each order information in the order information set 102 described above: and obtaining shelf information corresponding to each item name in the item name group included in the order information to obtain a shelf information group. Wherein the shelf information in the shelf information group includes a shelf identifier. Finally, the computing device 101 may combine each order information in the order information set 102, the target basket information corresponding to the order information, and the shelf information group to generate order sorting information, resulting in an order sorting information set 106.

Fig. 2 is another schematic diagram of an application scenario of an item sorting method according to some embodiments of the present disclosure.

In the application scenario of fig. 2, the system comprises a conveyor belt 1, a basket supply slide 2, a double-column stacker 3, an automatic basket scanner 4, a conveyor belt gate 5, an exit scanner 6, a lift 7, an automatic shelf 8, a basket exit slide 9-1, a basket exit slide 9-2, a basket exit slide 9-3 and a conveyor belt gate 10. The conveyor belt 1 includes an inner conveyor belt and an outer conveyor belt. In practice, first, a computing device (which may be, for example, a desktop computer, a laptop computer, etc.) may perform, for each order-sorting information in the order-sorting information set, the following sorting steps: the baskets corresponding to the order sorting information are transmitted into the outer side conveying belt of the conveying belt 1 from the basket supply slide 2, when the automatic basket scanner 4 scans the shelf numbers on the baskets, the corresponding conveying belt turn-gates 5 are opened, and then the baskets are moved to a carrying robot (not shown in the figure) below through the double-upright-column stacker 3 and are moved to the automatic shelf 8 for packing the goods. After the completion of the cargo packing, the cargo is moved to the inner conveyor by the lifter 7, followed by the cargo packing. And when the outlet scanner 6 scans that all the order sorting information corresponding to the goods basket is sorted, opening the turn door 10 of the conveying belt and conveying the goods basket to the outside conveying belt. And then the sorted goods baskets slide out through the goods basket outlet slide way 9-1, the goods basket outlet slide way 9-2 and the goods basket outlet slide way 9-3 so as to package the goods in the goods baskets.

The computing device 101 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of multiple servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices enumerated above. It may be implemented, for example, as multiple software or software modules to provide distributed services, or as a single software or software module. And is not particularly limited herein.

It should be understood that the number of computing devices in FIG. 1 is merely illustrative. There may be any number of computing devices, as implementation needs dictate.

With continued reference to fig. 3, a flow 300 of some embodiments of an item sorting method according to the present disclosure is shown. The method may be performed by the computing device 101 of fig. 1. The article sorting method comprises the following steps:

step 301, obtaining order information submitted by each user in the user group to obtain an order information set.

In some embodiments, an executing entity (e.g., the computing device 101 shown in fig. 1) of the item sorting method may obtain the order information submitted by each user in the user group from the terminal device through a wired connection or a wireless connection, so as to obtain the order information set. Wherein, the order information in the order information set comprises: an item name group, an item quantity group, and an item volume group. The item names in the item name group correspond to the item quantities in the item quantity group. The item names in the item name group correspond to the item volumes in the item volume group.

As an example, the order information set may be:

{ [ red wine, cola, cup ]; [10, 15, 12 ]; [ Diospermum arborescens, Diospermum;

{ [ television, air conditioner, refrigerator ]; [1, 2, 1 ]; [ 15dm et al, cultivation by weight ] }.

Here, the quantity of articles corresponding to red wine is "10" and the volume of articles corresponding to red wine is "[ 1dm for cultivation".

Step 302, generating total volume of the items based on the quantity group and volume group of the items included in each order information in the order information set, so as to obtain a total product set of the items.

In some embodiments, the executive agent may enable each order information in the order information set to a teammate to perform the following processing steps:

step one, determining a product value of the quantity of the articles corresponding to each article name and the volume of the articles included in the order information as the total volume of the single-type articles to obtain a total volume group of the single-type articles;

as an example, the order information may be: { [ red wine, cola, cup ]; [10, 15, 12 ]; [ thin plant according to dm, 2dm, 3dm et al ]. The product "10 dm" of the number of articles "10" and the volume of articles "1 dm" corresponding to the name of articles "red wine" may be determined as the total volume of the single type of articles. A product value of "30 dm" of quantity "15" and volume "2 dm" of the article corresponding to the article name "cola" may be determined as the total volume of the single type of article. The product value "36 dm" of the number of articles "12" and the volume of articles "3 dm" corresponding to the name of articles "cup" may be determined as the total volume of the single type of articles. Obtaining a total volume group of single type of articles: {10dm Abort under 30dm, 36dm }.

As another example, the order information may be: { [ television, air conditioner, refrigerator ]; [1, 2, 1 ]; [ 15dm et al, cultivation by weight ] }. The product "10 dm" of article quantity "1" and article volume "10 dm" corresponding to the article name "television" may be determined as the total volume of the single type of article. The product value "30 dm" of the article quantity "2" and the article volume "15 dm" corresponding to the article name "air conditioner" may be determined as the total volume of the single type of article. The product value "20 dm" of article quantity "1" and article volume "20 dm" corresponding to the article name "air conditioner" may be determined as the total volume of the single type of article. Obtaining a total volume group of single type of articles: {10dm Abort under 30 dm.

And secondly, determining the total volume of each single type of article in the total volume group of the single type of articles as the total volume of the articles.

As an example, the single type total volume group may be: {10dm Abort under 30dm, 36dm }. The total volume of each single species in group {10dm, 30dm, 36dm } may be determined as the total volume of the article "76 dm.

As another example, the single type total volume group may be: {10dm Abort under 30 dm. The total volume of each single species in group {10dm, 30dm, 20dm } may be determined as the total volume of the article "60 dm.

Thus, an overall product set of articles is obtained: {76dm Abort }.

And 303, selecting the basket information corresponding to the total volume of each article in the total volume of articles set as target basket information based on a preset basket information set to obtain a target basket information set.

In some embodiments, the execution main body may select, for each total volume of articles in the total volume of articles, basket information corresponding to the total volume of articles from a preset basket information set as target basket information. Thus, a target basket information set is obtained. Wherein, the basket information in the basket information set comprises a basket number and a basket volume. The basket information corresponding to the total volume of the articles may be basket information in which a basket volume included in the basket information is equal to or greater than the total volume of the articles and a difference between the basket volume included in the basket information and the total volume of the articles is smallest.

As an example, the basket information set may be:

{ [ No. 1 basket, 50dm bandpass; [ No. 2 basket, 60dm cultivation ]; [ No. 3 basket, 70dm cultivation ]; [ No. 4 basket, 80dm cultivation ]; [ No. 5 basket, 90dm cultivation ]; [ No. 6 basket, 100dm cultivation ] }.

The total collection of articles may be: {76dm Abort }.

The executing main body may be configured to thin down from a preset basket information set { [ basket No. 1, 50dm ]; [ No. 2 basket, 60dm cultivation ]; [ No. 3 basket, 70dm cultivation ]; [ No. 4 basket, 80dm cultivation ]; [ No. 5 basket, 90dm cultivation ]; and [6 th basket, 100dm ] selecting basket information corresponding to article total volume "76 dm" for carrying out dry cultivation [4 th basket, 80dm ] as target basket information.

The executing main body may be configured to thin down from a preset basket information set { [ basket No. 1, 50dm ]; [ No. 2 basket, 60dm cultivation ]; [ No. 3 basket, 70dm cultivation ]; [ No. 4 basket, 80dm cultivation ]; [ No. 5 basket, 90dm cultivation ]; and [6 th basket, 100dm ] selecting basket information corresponding to article total volume "60 dm" as target basket information [2 th basket, 60dm ] carrying out tope.

Thus, a target basket information set is obtained: { [ basket 4, 80dm ] A; [ No. 2 basket, 60dm cultivation ] }.

Step 304, for each order information in the order information set, executing the following processing steps: and obtaining shelf information corresponding to each item name in the item name group included in the order information to obtain a shelf information group.

In some embodiments, the executing agent may execute the following processing steps for each order information in the order information set: and acquiring shelf information corresponding to each item name in the item name group included in the order information from each item name included in the shelf information group stored in the terminal equipment in a wired connection mode or a wireless connection mode to obtain the shelf information group. Wherein the shelf information in the shelf information group includes a shelf identifier.

As an example, the shelf information group may be:

{ [ shelf No. 1] - [ red wine ] }; { [ shelf No. 2] - [ cola ] }; { [ shelf No. 3 ] - [ cup ] }; { [ shelf 4 ] - [ television ] }; { [ shelf No. 5 ] - [ air conditioner ] }; { [ shelf No. 6 ] - [ refrigerator ] }; { [ shelf No. 7 ] - [ item a ] }; { [ shelf No. 8 ] - [ C item ] }; { [ shelf 9 ] - [ D item ] }.

The executive body can determine order information { [ red wine, cola, cup ]; [10, 15, 12 ]; [ Diospermum arborescens, and the corresponding shelf information group is { [ shelf 1] - [ red wine ] }; { [ shelf No. 2] - [ cola ] }; { [ shelf No. 3 ] - [ cup ] } ".

The execution main body can determine order information { [ television, air conditioner, refrigerator ]; [1, 2, 1 ]; [10dm, 15dm, 20dm, et al, cultivation under thin circumstances ] } the corresponding shelf information set is "{ [ shelf 4 ] - [ television ] }; { [ shelf No. 5 ] - [ air conditioner ] }; { [ shelf No. 6 ] - [ refrigerator ] } ".

And 305, combining each order information in the order information set, the target basket information corresponding to the order information and the shelf information group to generate order sorting information, so as to obtain an order sorting information set.

In some embodiments, the executing entity may combine each order information in the order information set, the target basket information corresponding to the order information, and the shelf information group to generate order sorting information, so as to obtain an order sorting information set. Here, the combining process may refer to a splicing process.

As an example, the order information set may be:

{ [ red wine, cola, cup ]; [10, 15, 12 ]; [ Diospermum arborescens, Diospermum;

Order information { [ red wine, cola, cup ]; [10, 15, 12 ]; performing dry bottom year [1dm, 2dm, 3dm year ] }, target basket information "[ basket, 80dm, et al, flowering top year ] } corresponding to the order information, and shelf information set" { [ shelf ] - [ red wine ] }; { [ shelf No. 2] - [ cola ] }; the { [ shelf No. 3 ] - [ cup ] } "is combined to generate order sorting information" { [ red wine, cola, cup ]; [10, 15, 12 ]; undersea [1dm, 2dm, 3dm, according to an 80dm method of cultivating a fruit or plant by N.sub.4' - { [ 1H ] - [ Red wine ] } - { [ 2H ] - [ Cola ] } 3H ] - [ cup ] }.

The order information can be used for { [ television, air conditioner, refrigerator ]; [1, 2, 1 ]; performing dry bottom year [10dm, 15dm, 20dm plantation ] }, target basket information "[ basket, 60dm plantation ] } corresponding to the order information, and shelf information group" { [ shelf ] - [ television ] }; { [ shelf No. 5 ] - [ air conditioner ] }; the method comprises the following steps of { [6 shelf ] - [ refrigerator ] } "performing combined processing to generate order sorting information" { [ television, air conditioner, refrigerator ]; [1, 2, 1 ]; [10dm, 15dm, according to a method for carrying out heavy labor, 20dm, C.sub.2, 60dm, respectively, by carrying out fruit/plant ] - { [4 th shelf ] - [ TV ] } - { [5 th shelf ] - [ air conditioner ] } - { [6 th shelf ] - [ refrigerator ] }.

Thus, an order sorting information set is obtained:

{ [ red wine, cola, cup ]; [10, 15, 12 ]; undersea (C.A. [1dm, 2dm, 3dm, according to an FIGS. } 4, according to an 80dm method of bearing fruit by weight ] - { [1 st shelf ] - [ red wine ] } - { [2 nd shelf ] - [ cola ] } - { [3 th shelf ] - [ cup ] };

{ [ television, air conditioner, refrigerator ]; [1, 2, 1 ]; [10dm, 15dm, according to a method for carrying out heavy labor, 20dm, C.sub.2, 60dm, C.sub.H ] - { [4 th shelf ] - [ TV ] } - { [5 th shelf ] - [ air conditioner ] } - { [6 th shelf ] - [ refrigerator ] }.

With further reference to fig. 4, a flow 400 of further embodiments of an article sorting method according to the present disclosure is illustrated. The method may be performed by the computing device 101 of fig. 1. The article sorting method comprises the following steps:

step 401, obtaining order information submitted by each user in the user group to obtain an order information set.

Step 402, generating total volume of the articles based on the article quantity group and the article volume group included in each order information in the order information set, so as to obtain a total article volume set.

And step 403, selecting the basket information corresponding to the total volume of each article in the total volume of articles set as target basket information based on a preset basket information set to obtain a target basket information set.

Step 404, for each order information in the order information set, executing the following processing steps: and obtaining shelf information corresponding to each item name in the item name group included in the order information to obtain a shelf information group.

And 405, combining each order information in the order information set, the target basket information corresponding to the order information and the shelf information group to generate order sorting information, so as to obtain an order sorting information set.

In some embodiments, the specific implementation manner and technical effects of

steps

401 and 405 may refer to

steps

301 and 305 in those embodiments corresponding to fig. 3, which are not described herein again.

And 406, executing an article sorting operation according to each order sorting information in the order sorting information set.

In some embodiments, an executing entity of the item sorting method (e.g., computing device 101 shown in fig. 1) may perform the item sorting operation in accordance with each of the order sorting information sets described above in various ways.

In some optional implementations of some embodiments, the executing main body may perform, for each shelf information included in the order sorting information, the following sorting steps:

the method comprises a first step of adding order sorting information into a preset sorting information queue and updating the sorting information queue in response to receiving detection information corresponding to the shelf information and sent by an image acquisition device. Here, the image pickup device may refer to an image pickup device having an image pickup function and a recognition function. Here, the sorting information queue may refer to order sorting information to be sorted.

And a second step of marking the sorting state of the article name corresponding to the shelf information in the order sorting information as a sorting completion state in response to receiving information which represents sorting completion and is sent by the sorting robot. Here, the sorting robot may be a warehouse logistics robot, an intelligent transfer robot AGV.

And a third step of determining the order sorting information as the order information to be packaged in response to detecting that the name of the article in the unsorted state does not exist in the order sorting information.

And a fourth step of executing the sorting step again in response to detecting that the article name in the to-be-sorted state exists in the order sorting information.

Step 407, for each determined order information to be packaged, executing the following processing steps: selecting at least one article name corresponding to the article type and the packaging type from the to-be-packaged order information as a classified article name group based on each packaging type in a preset packaging type group to obtain a classified article name group set; and controlling the associated packaging equipment to perform packaging operation on each article corresponding to the classified article name group based on the packaging type corresponding to each classified article name group in the classified article name group set.

In some embodiments, the order information in the order information set further comprises: and the article type in the article type group corresponds to the article name in the article name group. Here, the item type may refer to a category of the item, for example, the item type of red wine may be "wine type". The executing agent may execute the following processing steps for each determined order information to be packaged:

the method comprises the steps of firstly, selecting at least one article name corresponding to the article type and the packaging type from the to-be-packaged order information as a classified article name group based on each packaging type in a preset packaging type group, and obtaining a classified article name group set.

In practice, the above-mentioned first step may comprise the following sub-steps:

the first sub-step, carry on the encoding process to the above-mentioned encapsulation type in order to produce the encapsulation type of code. Here, the encoding process may be semantic encoding using NNLM (Neural Network Language Model) or may be a process of inverting a word vector after unique hot encoding. For example, the one-hot encoded word vector may be [1000010], and flipping the word vector [1000010] may result in [0111101 ].

And a second substep of performing encoding processing on each item type in the item type group included in the order information to be packaged to generate an encoded item type, so as to obtain an encoded item type group. Here, the encoding process may be semantic encoding using a neural network language model, or may be a process of inverting a word vector after unique hot encoding.

A third substep of determining a relationship distance value between each encoded item type in the set of encoded item types and the encoded package type to obtain a set of relationship distance values.

In practice, the execution body may generate the relational distance value between the coded article type and the coded package type according to the following formula:

。

wherein the content of the first and second substances,

representing a first distance value.

Representing a second distance value.

Representing a third distance value.

Indicating the number of characters included in the coded article type or the number of characters included in the coded package type.

A serial number indicating a character included in the coded article type or a serial number indicating a character included in the coded package type.

Indicating the type of coded item

And (4) characters.

Representing the mean value of the individual characters comprised by the above-mentioned coded item type.

Indicating the type of coded encapsulation mentioned above

And (4) characters.

Which represents the average value of the individual characters included in the above-described coded package type.

Representing a relational distance value.

And a fourth substep of selecting a relationship distance value greater than or equal to a preset distance value from the relationship distance value set as a target relationship distance value to obtain a target relationship distance value set. Here, the setting of the preset distance value is not limited.

And a fifth substep of determining the article name corresponding to each target relationship distance value in the target relationship distance value groups as a classified article name to obtain a classified article name group.

And secondly, controlling related packaging equipment to perform packaging operation on each article corresponding to the classified article name group based on the packaging type corresponding to each classified article name group in the classified article name group set. In practice, the execution main body may control a packaging device, which is in communication connection with the execution main body and is preset to correspond to the packaging type of the classified item name group, to perform a packaging operation on each item corresponding to the classified item name group. Here, the packaging apparatus may be a warehouse logistics robot, a smart packaging robot.

The formula and its related content in step 407 are used as an invention of the present disclosure, thereby solving the technical problem mentioned in the background art two, "the different types of articles are not classified and packaged, which results in high loss of other articles when some articles (e.g., beverage wine) are damaged". Factors that contribute to higher wear of other items tend to be as follows: the different types of articles are not classified and packaged, resulting in high wastage of other articles when some of the articles (e.g. beverage wine) are damaged. If the above factors are solved, the effect of reducing the loss of other articles can be achieved. To achieve this effect, the article sorting method of some embodiments of the present disclosure, first, performs encoding processing on each article type in the package type and the article type group. Thereby, subsequent calculation of a value of a relationship between the package type and the item type is facilitated. Here, because different article types have different packaging manners, i.e. correspond to different packaging types. Therefore, the articles with the same packaging type can be packaged together, so that the packaging cost is saved, and the loss of other articles caused by the damage of part of the articles (such as beverage wine) is avoided. Then, the relationship distance value between the type of the article and the packaging type is comprehensively considered through three angles so as to package the articles with the same packaging type together. Here, a loss value from the character mean is calculated using each character in the coded item type and each character in the coded package type, respectively, to find the first distance value. Here, a comprehensive solution is performed using each character in the encoded item type and each character in the encoded package type to generate a second distance value. Here, each character in the coded article type and each character in the coded package type are reused to obtain a third distance value through a relational distance formula. And finally, taking the average value of the three distance values as a relation distance value. Thus, articles having the same packaging type can be accurately packaged together. Furthermore, the loss of other articles in the transportation process is reduced.

Optionally, the order information in the order information set further includes: and (4) address information. The address information may be shipping address information.

Optionally, based on each address information included in the determined order information to be packaged, clustering each order information to be packaged in the determined order information to be packaged is performed, so as to obtain a clustered order information group set to be packaged.

In some embodiments, the executing agent may perform clustering processing on each piece of order information to be packaged in the determined order information to be packaged based on each piece of address information included in the determined order information to be packaged, so as to obtain a clustered order information group set to be packaged. In practice, the executing entity may cluster the order information to be packaged, of which the address information belongs to the same dimension (for example, belongs to the same city), into a cluster order information group to be packaged, so as to obtain a cluster order information group set to be packaged.

Optionally, based on the total volume of each article corresponding to each clustered order information group to be packaged in the clustered order information group set, a total volume of article classification is generated, so as to obtain a total product set of article classification.

In some embodiments, the executing body may determine a total sum of total volumes of the articles corresponding to each clustered order information group to be packaged in the clustered order information group set as a total volume of the article classification, so as to obtain a total product set of the article classification.

Optionally, based on each clustered order information group to be packaged in the clustered order information group set, vehicle information matched with the clustered order information group to be packaged is selected from a preset vehicle information set to serve as target vehicle information, and a target vehicle information set is obtained.

In some embodiments, the vehicle information in the vehicle information set includes vehicle volume information. Here, the vehicle volume information may refer to a maximum volume that the vehicle can accommodate. Based on each clustered order information group to be packaged in the clustered order information group set, the execution main body may select, from a preset vehicle information set, vehicle information matched with the clustered order information group to be packaged as target vehicle information through the following steps:

the first step is to perform encoding processing on the vehicle volume information included in each piece of vehicle information in the vehicle information sets to generate encoded vehicle volume information, and obtain encoded vehicle volume information sets. Here, the encoding process may be semantic encoding using a neural network language model, or may be a process of inverting a word vector after unique hot encoding.

And secondly, coding the total volume of the classified articles corresponding to the clustered order information group to be packaged to generate the total volume of the coded articles. Here, the encoding process may be semantic encoding using a neural network language model, or may be a process of inverting a word vector after unique hot encoding.

And thirdly, generating a correlation value between each piece of coded vehicle volume information in the coded vehicle volume information set and the coded article classification total volume to obtain a correlation value set.

In practice, the third step may generate the correlation value between the coded vehicle volume information and the total classified volume of the coded articles by the following formula:

。

wherein the content of the first and second substances,

representing the associated value.

And a serial number indicating a character included in the coded vehicle volume information or a serial number indicating a character included in the total volume of the coded article classification.

The number of characters included in the coded vehicle volume information or the number of characters included in the total volume of the coded article classification is represented.

Means for indicating that the coded vehicle volume information includes

And (4) characters.

Indicating the total volume included in said classification of coded articles

And (4) characters.

And fourthly, determining the correlation value with the maximum value in the correlation value set as the target correlation value.

And fifthly, determining the vehicle information corresponding to the target correlation value as target vehicle information.

The formula and the related content in the optional content are taken as an invention point of the disclosure, thereby solving the technical problems mentioned in the background technology, namely, the problem that the transportation vehicles are not reasonably selected, which causes the possibility of repeatedly dispatching the vehicles for transportation and wastes transportation resources. The factors causing the waste of transportation resources are often as follows: transport vehicles are not reasonably selected, so that the vehicles may need to be repeatedly scheduled for transportation, and the waste of transportation resources is caused. If the above factors are solved, the effect of reducing the waste of transportation resources can be achieved. In order to achieve this effect, in the article sorting method according to some embodiments of the present disclosure, first, based on each address information included in the determined order information to be packaged, clustering is performed on each order information to be packaged in the determined order information to be packaged, so as to obtain a clustered order information group to be packaged. Therefore, all articles corresponding to the to-be-packaged order information of the same type of address information can be gathered together for unified delivery, and repeated vehicle dispatching is avoided preliminarily for transportation. And secondly, generating a total volume of the classified articles based on the total volume of the articles corresponding to each clustered order information group to be packaged in the clustered order information group set, so as to obtain a total product set of the classified articles. And then, based on each clustering order information group to be packaged in the clustering order information group to be packaged, selecting the vehicle information matched with the clustering order information group to be packaged from a preset vehicle information set as target vehicle information to obtain a target vehicle information set. Thus, a vehicle meeting the transportation requirements can be selected. Further, a correlation value between the coded vehicle volume information and the coded article classification total volume is generated by using a passage formula. The selected transport vehicle can be more appropriate to the article to be transported, and the waste of transport resources is further avoided. And finally, controlling the related carrying robot to carry out boxing operation on each packaged article corresponding to the clustering order information group to be packaged corresponding to the target vehicle information based on each piece of target vehicle information in the target vehicle information set. Thereby, the boxing operation of the articles to be transported is completed. Through the steps, the transport vehicles can be reasonably selected, repeated scheduling of the vehicles is avoided, and waste of transport resources is reduced.

As can be seen from fig. 4, the flow 400 of the item sorting method in some embodiments corresponding to fig. 4 completes the packing operation of the items to be transported, compared to the description of some embodiments corresponding to fig. 3. Through the steps, the transport vehicles can be reasonably selected, repeated scheduling of the vehicles is avoided, and waste of transport resources is reduced.

With further reference to fig. 5, as an implementation of the methods illustrated in the above figures, the present disclosure provides some embodiments of an article sorting apparatus, which correspond to those method embodiments described above with reference to fig. 3, and which may be particularly applicable in various electronic devices.

As shown in fig. 5, the article sorting apparatus 500 of some embodiments includes: a first acquisition unit 501, a generation unit 502, a selection unit 503, a second acquisition unit 504, and a combination unit 505. The first obtaining unit 501 is configured to obtain order information submitted by each user in a user group, and obtain an order information set, where the order information in the order information set includes: the system comprises an article name group, an article quantity group and an article volume group, wherein the article name in the article name group corresponds to the article quantity in the article quantity group, and the article name in the article name group corresponds to the article volume in the article volume group; the generating unit 502 is configured to generate a total volume of the items based on the quantity group and the volume group of the items included in each order information in the order information set, so as to obtain a total volume set of the items; the selection unit 503 is configured to select, based on a preset basket information set, basket information corresponding to a total volume of each article in the total volume of articles as target basket information to obtain a target basket information set, where the basket information in the basket information set includes a basket number and a basket volume; the second obtaining unit 504 is configured to perform, for each order information in the order information set, the following processing steps: acquiring shelf information corresponding to each item name in an item name group included in the order information to obtain a shelf information group, wherein the shelf information in the shelf information group includes shelf identification; the combining unit 505 is configured to combine each order information in the order information set, the target basket information corresponding to the order information, and the shelf information group to generate order sorting information, resulting in an order sorting information set.

It will be understood that the elements described in the apparatus 500 correspond to various steps in the method described with reference to fig. 3. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 500 and the units included therein, and are not described herein again.

Referring now to FIG. 6, a block diagram of an electronic device (e.g., computing device 101 of FIG. 1) 600 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic device shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.

As shown in fig. 6, electronic device 600 may include a processing means (e.g., central processing unit, graphics processor, etc.) 601 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage means 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the electronic apparatus 600 are also stored. The processing device 601, the ROM602, and the RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.

Generally, the following devices may be connected to the I/O interface 605: input devices 606 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 607 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 608 including, for example, tape, hard disk, etc.; and a communication device 609. The communication means 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. While fig. 6 illustrates an electronic device 600 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 6 may represent one device or may represent multiple devices as desired.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network through the communication device 609, or installed from the storage device 608, or installed from the ROM 602. The computer program, when executed by the processing device 601, performs the above-described functions defined in the methods of some embodiments of the present disclosure.

It should be noted that the computer readable medium described above in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.

In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.

The computer readable medium may be embodied in the apparatus; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: obtaining order information submitted by each user in a user group to obtain an order information set, wherein the order information in the order information set comprises: the system comprises an article name group, an article quantity group and an article volume group, wherein the article name in the article name group corresponds to the article quantity in the article quantity group, and the article name in the article name group corresponds to the article volume in the article volume group; generating total volume of the articles based on the article quantity group and the article volume group included in each order information in the order information set to obtain a total article volume set; selecting basket information corresponding to the total volume of each article in the total volume of articles set as target basket information based on a preset basket information set to obtain a target basket information set, wherein the basket information in the basket information set comprises a basket number and a basket volume; for each order information in the order information set, executing the following processing steps: acquiring shelf information corresponding to each item name in an item name group included in the order information to obtain a shelf information group, wherein the shelf information in the shelf information group includes shelf identification; and combining each order information in the order information set, the target basket information corresponding to the order information and the goods shelf information group to generate order sorting information to obtain an order sorting information set.

Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

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 and/or flowchart illustration, and combinations of blocks in the block diagrams and/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.

The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes a first acquisition unit, a generation unit, a selection unit, a second acquisition unit, and a combination unit. Where the names of the units do not in some cases constitute a limitation on the units themselves, for example, the generating unit may also be described as "a unit that generates a total volume of the items based on the number group and volume group of the items included in each order information in the order information set described above, resulting in a total volume set of the items".

The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.

The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.

Claims

1. A method of sorting articles, comprising:

obtaining order information submitted by each user in a user group to obtain an order information set, wherein the order information in the order information set comprises: the system comprises an article name group, an article quantity group and an article volume group, wherein the article name in the article name group corresponds to the article quantity in the article quantity group, and the article name in the article name group corresponds to the article volume in the article volume group;

generating total volume of the articles based on the article quantity group and the article volume group included in each order information in the order information set to obtain a total article volume set;

selecting basket information corresponding to the total volume of each article in the total volume of articles set as target basket information based on a preset basket information set to obtain a target basket information set, wherein the basket information in the basket information set comprises a basket number and a basket volume;

for each order information in the order information set, performing the following processing steps:

acquiring shelf information corresponding to each item name in an item name group included in the order information to obtain a shelf information group, wherein the shelf information in the shelf information group includes shelf identification;

and combining each order information in the order information set, the target basket information corresponding to the order information and the goods shelf information group to generate order sorting information to obtain an order sorting information set.

2. The method of claim 1, wherein the method further comprises:

and executing article sorting operation according to each order sorting information in the order sorting information set.

3. The method of claim 2, wherein said performing an item sorting operation from each order sorting information in said set of order sorting information comprises:

for each shelf information comprised by the order sorting information, performing the following sorting steps:

in response to receiving detection information corresponding to the shelf information and sent by an image acquisition device, adding the order sorting information to a preset sorting information queue, and updating the sorting information queue;

in response to receiving information which represents that sorting is finished and is sent by a sorting robot, marking the sorting state of the article name corresponding to the shelf information in the order sorting information as a sorting finished state;

in response to detecting that no article name in an unsorted state exists in the order sorting information, determining the order sorting information as order information to be packaged.

4. The method of claim 3, wherein the method further comprises:

and in response to detecting that the article names in the to-be-sorted state exist in the order sorting information, executing the sorting step again.

5. The method of claim 4, wherein the order information in the order information set further comprises: the article type group, the article type in the article type group corresponds to the article name in the article name group; and

the method further comprises the following steps:

for each determined order information to be packaged, the following processing steps are performed:

selecting at least one article name corresponding to the article type and the packaging type from the to-be-packaged order information as a classified article name group based on each packaging type in a preset packaging type group to obtain a classified article name group set;

and controlling the associated packaging equipment to perform packaging operation on each article corresponding to the classified article name group based on the packaging type corresponding to each classified article name group in the classified article name group set.

6. The method according to claim 5, wherein the selecting at least one item name of which the item type corresponds to the packaging type from the order information to be packaged as a classified item name group based on each packaging type in a preset packaging type group comprises:

encoding the encapsulation type to generate an encoded encapsulation type;

coding each article type in the article type group included in the order information to be packaged to generate a coded article type, so as to obtain a coded article type group;

determining a relationship distance value between each coded article type in the coded article type group and the coded packaging type to obtain a relationship distance value group;

selecting a relation distance value which is greater than or equal to a preset distance value from the relation distance value group as a target relation distance value to obtain a target relation distance value group;

and determining the article name corresponding to each target relationship distance value in the target relationship distance value group as a classified article name to obtain a classified article name group.

7. The method of claim 5, wherein the order information in the order information set further comprises: address information; and

the method further comprises the following steps:

based on each address information included in the determined order information to be packaged, clustering each order information to be packaged in the determined order information to be packaged to obtain a clustered order information group set to be packaged;

generating a total volume of article classification based on the total volume of each article corresponding to each clustered order information group to be packaged in the clustered order information group set to obtain a total product set of article classification;

based on each clustering order information group to be packaged in the clustering order information group set to be packaged, selecting vehicle information matched with the clustering order information group to be packaged from a preset vehicle information set as target vehicle information to obtain a target vehicle information set;

and controlling the related carrying robot to carry out boxing operation on each packaged article corresponding to the clustered order information group to be packaged corresponding to the target vehicle information based on each piece of target vehicle information in the target vehicle information set.

8. An article sorting apparatus comprising:

the first obtaining unit is configured to obtain order information submitted by each user in a user group, and obtain an order information set, wherein the order information in the order information set comprises: the system comprises an article name group, an article quantity group and an article volume group, wherein the article name in the article name group corresponds to the article quantity in the article quantity group, and the article name in the article name group corresponds to the article volume in the article volume group;

a generating unit configured to generate a total volume of the items based on the quantity group and the volume group of the items included in each order information in the order information set, so as to obtain a total volume set of the items;

the selection unit is configured to select basket information corresponding to the total volume of each article in the total volume of articles as target basket information based on a preset basket information set to obtain a target basket information set, wherein the basket information in the basket information set comprises a basket number and a basket volume;

a second acquisition unit configured to perform, for each order information in the order information set, the following processing steps: acquiring shelf information corresponding to each item name in an item name group included in the order information to obtain a shelf information group, wherein the shelf information in the shelf information group includes shelf identification;

and the combining unit is configured to combine each order information in the order information set, the target basket information corresponding to the order information and the shelf information group to generate order sorting information, so as to obtain an order sorting information set.

9. An electronic device, comprising:

one or more processors;

a storage device having one or more programs stored thereon;

when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-7.

10. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-7.