CN113610448A - Article scheduling method and device, electronic equipment and computer readable medium - Google Patents
Article scheduling method and device, electronic equipment and computer readable medium Download PDFInfo
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Abstract
The embodiment of the disclosure discloses an article scheduling method, an article scheduling device, electronic equipment and a computer readable medium. One embodiment of the method comprises: determining whether stores meeting a first scheduling condition exist in stores in the target area in response to the current time being the scheduling time; in response to the determination that the shop meets the first scheduling condition, determining the shop meeting the first scheduling condition as an alternative shop, and obtaining an alternative shop set; acquiring a target article information group corresponding to each alternative shop in the alternative shop sets to obtain a target article information group set; determining an alternative article information group set corresponding to the target article information group set according to each article information group corresponding to each shop; and controlling the related transfer robot to dispatch each article corresponding to the candidate article information group set according to each candidate shop corresponding to the target article information group set. This embodiment reduces waste of store space resources.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of computers, in particular to an article scheduling method, an article scheduling device, electronic equipment and a computer readable medium.
Background
Currently, the stock method of each shop in a target area (for example, a dish market) generally adopts the following methods: according to the article flow of the previous day, the article flow of the next day is predicted, and then the articles are fed according to the predicted article flow, so that the overstock and the loss of the articles are reduced.
However, with the above method, there are generally the following technical problems:
firstly, when the quantity of articles purchased by part of shops is less than the quantity required by a user, the shops are idle in a certain time, and the space resources of the shops are wasted;
second, when the quantity of the purchased goods in some shops is larger than the quantity required by the user, the overstock and the loss of the goods are caused.
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 item scheduling methods, apparatuses, electronic devices and computer readable media 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 an article scheduling method, including: determining whether stores meeting a first scheduling condition exist in stores in the target area in response to the current time being the scheduling time; in response to the determination of existence, determining the stores meeting the first scheduling condition in the stores as alternative stores to obtain alternative store pavements; acquiring a target article information group corresponding to each alternative shop in the alternative shop set to obtain a target article information group set; determining a candidate item information group set corresponding to the target item information group set according to each item information group corresponding to each store, wherein the item information group in each item information group corresponds to a store in each store; and controlling the related transfer robot to dispatch each article corresponding to the candidate article information group set according to each candidate shop corresponding to the target article information group set.
In a second aspect, some embodiments of the present disclosure provide an article scheduling apparatus, the apparatus comprising: a first determination unit configured to determine whether there is a store satisfying a first scheduling condition among stores in the target area in response to a current time being a scheduling time; a second determination unit configured to determine, in response to determination of presence, a store satisfying the first scheduling condition among the stores as an alternative store, resulting in an alternative store deck; an acquisition unit configured to acquire a target article information group corresponding to each of the candidate stores in the candidate store set to obtain a target article information group set; a third specifying unit configured to specify a candidate item information group set corresponding to the target item information group set, based on each item information group corresponding to each store, wherein an item information group in each item information group corresponds to a store in each store; and a control unit configured to control the associated transfer robot to dispatch each item corresponding to the candidate item information group set, based on each candidate store corresponding to the target item information group 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 scheduling method of some embodiments of the present disclosure, waste of store space resources is reduced. Specifically, the reasons for the waste of store space resources are: when the quantity of articles purchased by part of shops is less than the quantity required by users, the shops are idle in a certain time, and the space resources of the shops are wasted. Based on this, the item scheduling method of some embodiments of the present disclosure first determines whether there is a store that satisfies a first scheduling condition among stores in the target area in response to the current time being a scheduling time. Next, in response to determining that there is a store, identifying a store satisfying the first scheduling condition among the stores as a candidate store, and obtaining a candidate store deck. Thus, the shop satisfying the first scheduling condition in the target area can be specified. That is, an idle store may be determined. And then, acquiring a target article information group corresponding to each candidate shop in the candidate shop set to obtain a target article information group set. Thereby, the item information of the item to be replenished in the alternative shop is facilitated to be determined. Then, a candidate item information group set corresponding to the target item information group set is specified from each item information group corresponding to each store. Wherein the article information groups in the article information groups correspond to stores in the stores. Therefore, the articles corresponding to the target article information in other shops in the target area can be determined, and subsequent article scheduling is facilitated. And finally, controlling the related transfer robot to dispatch each article corresponding to the candidate article information group set according to each candidate shop corresponding to the target article information group set. Thus, the articles in other stores can be dispatched to the idle store. Thus, the waste of space resources of the shop is reduced.
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.
FIG. 1 is a schematic illustration of one application scenario of an item scheduling method of some embodiments of the present disclosure;
fig. 2 is a flow diagram of some embodiments of an item scheduling method according to the present disclosure;
FIG. 3 is a flow diagram of further embodiments of an item scheduling method according to the present disclosure;
FIG. 4 is a schematic block diagram of some embodiments of an item scheduling apparatus according to the present disclosure;
FIG. 5 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 scheduling method according to some embodiments of the present disclosure.
In the application scenario of fig. 1, first, the computing device 101 may determine whether there is a store that satisfies a first scheduling condition among stores in the target area in response to the current time being a scheduling time. Next, the computing device 101 may determine, as candidate stores, stores satisfying the first scheduling condition among the stores, in response to determining that there is a store, resulting in a shop of candidate stores. Next, the computing device 101 may obtain a target item information group corresponding to each candidate store in the candidate store set to obtain a target item information group set 102. Then, the computing device 101 may identify the candidate item information group set 104 corresponding to the target item information group set 102 from each item information group 103 corresponding to each store. The article information groups in the article information groups 103 correspond to stores in the stores. Finally, the computing device 101 may control the associated carrier robot to dispatch each item corresponding to the candidate item information group set 104 according to each candidate store corresponding to the target item information group set 102.
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. 2, a flow 200 of some embodiments of an item scheduling method according to the present disclosure is shown. The article scheduling method comprises the following steps:
In some embodiments, an executing subject of the item scheduling method (e.g., the computing device 101 shown in fig. 1) may determine whether there is a store that satisfies the first scheduling condition among stores within the target area in response to the current time being a scheduling time. Here, the scheduling time may refer to a time set in advance for article scheduling. For example, the scheduled time may be 18 pm each day. Here, the target area may be an area including each shop divided in advance. For example, the target area may be a vegetable market. Here, the first scheduling condition may be "the item scheduling request is issued by the store terminal corresponding to the store". Here, the item scheduling request may be an item replenishment request transmitted from the store terminal to the execution main body. Here, the item scheduling request may be a request for restocking of items issued by the store. Here, each of the stores is a store that includes a plurality of articles and is individually restocked. Here, the store terminal may refer to a computer device in the store. In practice, the executing agent may determine whether there is a store satisfying the first scheduling condition among the stores in the target area in response to the current time being the scheduling time. That is, it is detected whether or not there is a store satisfying "the article scheduling request is issued by the store terminal corresponding to the store" among the stores in the target area.
And 202, in response to the determination of existence, determining the stores meeting the first scheduling condition from the stores as alternative stores to obtain alternative store pavements.
In some embodiments, the execution subject may determine, as an alternative store, a store satisfying the first scheduling condition among the stores, in response to determining that the store exists, to obtain an alternative store deck.
As an example, each store may be "store A, store B, store C, store D, store E, store F, store G, store H". For example, "store a, store B" in each store satisfies the first scheduling condition described above. Thus, "store a and store B" can be identified as candidate stores, and a candidate store set can be obtained.
In some embodiments, the execution subject may obtain the target item information group set by obtaining the target item information group corresponding to each candidate store from the store terminal corresponding to each candidate store in the candidate store set by means of wired connection or wireless connection. Here, the target item information in the target item information group may be information of an item to be restocked in the store. Here, the target item information may include, but is not limited to: alternative store identification, item name, and item demand. Here, the item demand may refer to the amount of the item that needs to be replenished.
As an example, the set of target item information groups may be:
{ [ store A, item a: 10 ]; [ store A, item b: 8] };
{ [ store B, item: 11 ]; [ store B, item: 15]}.
And step 204, determining a candidate article information group set corresponding to the target article information group set according to each article information group corresponding to each shop.
In some embodiments, the execution subject may determine the candidate item information group set corresponding to the target item information group set according to each item information group corresponding to each store. Wherein the article information groups in the article information groups correspond to stores in the stores. In practice, first, the execution subject may obtain the item information group from the store terminal corresponding to each store by wired connection or wireless connection. Thus, each item information group corresponding to each store is obtained. Here, the item information in the item information group may include, but is not limited to: store identification, item name, and item remaining amount. Here, the remaining quantity of the item may be a predicted remaining quantity of a certain item in the store on the day.
Next, for each target item information in the target item information group, the executing body may execute the following processing steps:
first, item information including an item name identical to the item name included in the target item information is selected from the item information groups as first item information, and a first item information group is obtained.
And a second step of selecting first item information including the largest remaining quantity of items from the first item information group as second item information.
And thirdly, performing association processing on the second article information and the alternative shop identification included in the target article information to obtain associated article information serving as alternative article information. Here, the association process may refer to a splicing process.
Finally, the execution subject may group the candidate item information items having the same candidate store identifier included in the obtained candidate item information items into one group to generate a candidate item information group, thereby obtaining a candidate item information group set.
And step 205, controlling the related transfer robot to dispatch each article corresponding to the candidate article information group set according to each candidate shop corresponding to the target article information group set.
In some embodiments, for each of the alternative stores, the executing entity may perform the following processing steps:
first, a candidate item information group including a candidate store identifier identical to the store identifier of the candidate store is selected from the candidate item information group set.
In the second step, for each target item information corresponding to the candidate store, first, the execution agent may select, as the item information to be scheduled, candidate item information including an item name identical to an item name included in the target item information from the candidate item information group. Then, the executive body can control the associated transfer robot to transfer the objects represented by the target number of the object information to be dispatched from the stores corresponding to the object information to be dispatched so as to transport the objects to the alternative stores. Here, when the required quantity of the items included in the target item information is equal to or less than the remaining quantity of the items included in the item information to be dispatched, the target quantity is the required quantity of the items included in the target item information. And when the article demand quantity included in the target article information is greater than the article residual quantity included in the article information to be dispatched, the target quantity is the article residual quantity included in the article information to be dispatched. Here, the associated transfer robot may sometimes refer to a transfer apparatus that is communicatively connected to the execution main body described above. For example, the transfer robot may be an agv (automated Guided vehicle) cart or a warehouse logistics robot.
The above embodiments of the present disclosure have the following advantages: by the article scheduling method of some embodiments of the present disclosure, waste of store space resources is reduced. Specifically, the reasons for the waste of store space resources are: when the quantity of articles purchased by part of shops is less than the quantity required by users, the shops are idle in a certain time, and the space resources of the shops are wasted. Based on this, the item scheduling method of some embodiments of the present disclosure first determines whether there is a store that satisfies a first scheduling condition among stores in the target area in response to the current time being a scheduling time. Next, in response to determining that there is a store, identifying a store satisfying the first scheduling condition among the stores as a candidate store, and obtaining a candidate store deck. Thus, the shop satisfying the first scheduling condition in the target area can be specified. That is, an idle store may be determined. And then, acquiring a target article information group corresponding to each candidate shop in the candidate shop set to obtain a target article information group set. Thereby, the item information of the item to be replenished in the alternative shop is facilitated to be determined. Then, a candidate item information group set corresponding to the target item information group set is specified from each item information group corresponding to each store. Wherein the article information groups in the article information groups correspond to stores in the stores. Therefore, the articles corresponding to the target article information in other shops in the target area can be determined, and subsequent article scheduling is facilitated. And finally, controlling the related transfer robot to dispatch each article corresponding to the candidate article information group set according to each candidate shop corresponding to the target article information group set. Thus, the articles in other stores can be dispatched to the idle store. Thus, the waste of space resources of the shop is reduced.
With further reference to fig. 3, further embodiments of an item scheduling method according to the present disclosure are illustrated. The article scheduling method comprises the following steps:
In some embodiments, the specific implementation and technical effects of steps 301 and 303 can refer to steps 201 and 203 in the embodiments corresponding to fig. 2, which are not described herein again.
In some embodiments, an executing subject (e.g., the computing device 101 shown in fig. 1) of the item scheduling method may remove item information whose store identification included in each item information group is the same as that included in the target item information to update each item information group. Wherein the article information groups in the article information groups correspond to stores in the stores. The article information in each article information group includes a shop identifier, an article name, an article circulation amount corresponding to the article name, an article number, and an article prediction amount. The target item information in the target item information set includes a store identifier, an item name, and an item adjustment amount. Here, the article circulation amount may refer to the amount (number of article sales) that the article represented by the article information is currently circulated (circulation is started today). Here, the item number may refer to a number currently remaining for the item characterized by the item information. Here, the article forecast amount may refer to the amount of articles forecasted in advance that are distributed (sold) today. Here, the item adjustment amount may refer to the number of items currently to be restocked. In practice, the execution subject may remove item information whose store identifier included in each item information group is the same as the store identifier included in the target item information, so as to update each item information group.
In some embodiments, the execution subject may select, from the updated respective article information groups, article information satisfying the second scheduling condition as initial article information, to obtain an initial article information group. Wherein the second scheduling condition is: the item name included in the item information is the same as the item name included in the target item information.
In some embodiments, for each initial item information in the initial item information group, based on an item traffic amount, an item number, and an item prediction amount included in the initial item information, the execution body may generate an item remaining amount corresponding to the initial item information by:
the first step, the sum of the article flow and the article quantity is determined as the total article quantity.
And secondly, determining the difference value between the total quantity of the articles and the predicted quantity of the articles as the residual quantity of the articles.
Step 3044, selecting the remaining quantity of articles greater than the preset threshold from the generated remaining quantities of articles as the remaining quantity of alternative articles, and obtaining a group of remaining quantities of alternative articles.
In some embodiments, the execution subject may select, from the generated remaining quantity of each item, a remaining quantity of the item greater than a preset threshold as a remaining quantity of an alternative item, to obtain a remaining quantity of the alternative item group. Wherein the preset threshold is 0.
In some embodiments, the execution subject may generate at least one item candidate information corresponding to the target item information according to the item adjustment amount included in the item candidate remaining amount group and the target item information. Wherein, the at least one alternative article information has an arrangement order.
In practice, according to the remaining quantity group of the candidate items and the item adjustment quantity included in the target item information, the executing body may generate at least one piece of candidate item information corresponding to the target item information by:
in response to the fact that the sum of the remaining quantities of all the alternative articles in the remaining quantity group of the alternative articles is smaller than or equal to the article blending quantity, determining initial article information corresponding to the remaining quantity of each alternative article in the remaining quantity group of the alternative articles as first article information to obtain a first article information group. In practice, first, the execution body may determine a sum of the remaining amounts of the respective alternative items included in the group of the remaining amounts of the alternative items. Then, in response to determining that the sum of the remaining quantities of the various alternative articles included in the remaining quantity group of alternative articles is less than or equal to the article blending quantity, the initial article information corresponding to each remaining quantity of the alternative articles in the remaining quantity group of alternative articles may be determined as the first article information, so as to obtain a first article information group.
And secondly, performing association processing on each first article information in the first article information group and the shop mark included in the target article information to generate associated article information serving as alternative article information to obtain an alternative article information group. Here, the association process may refer to a splicing process. For example, the first item information may be [ F store, a item, item circulation amount: 125, number of items: 25, item pre-measurement: 135]. The target item information may be [ store a, item adjustment amount: 12]. The first item information [ store, item traffic: 125, number of items: 25, item pre-measurement: 135] and the target item information [ store, item a, item adjustment amount: 12]. The included store identification "store a" performs association processing to generate associated item information "[ store F, item a, item circulation amount: 125, number of items: 25, item pre-measurement: 135] - [ store a ] "as alternative item information.
In some optional implementation manners of some embodiments, according to the remaining quantity group of the alternative items and the item adjustment quantity included in the target item information, the executing body may further generate at least one alternative item information corresponding to the target item information by:
the method comprises a first step of responding to the fact that the sum of the remaining quantity of each alternative item included in the group of the remaining quantity of the alternative item is larger than the item adjusting quantity, and determining whether the remaining quantity of the alternative item which is larger than or equal to the item adjusting quantity exists in the group of the remaining quantity of the alternative item.
And secondly, in response to the fact that the alternative article residual quantity which is greater than or equal to the article adjusting quantity exists in the alternative article residual quantity group, determining the alternative article residual quantity which is greater than or equal to the article adjusting quantity in the alternative article residual quantity group as a first article residual quantity to obtain a first article residual quantity group.
And thirdly, determining the initial article information corresponding to the first article residual quantity with the largest value in the first article residual quantity group as second article information.
And a fourth step of performing association processing on the second item information and the shop mark included in the target item information to generate associated item information as candidate item information. Here, the association process may refer to a splicing process.
In some optional implementation manners of some embodiments, according to the remaining quantity group of the alternative items and the item adjustment quantity included in the target item information, the executing body may further generate at least one alternative item information corresponding to the target item information by:
the method comprises the steps of firstly, responding to the situation that the sum of the residual quantity of each alternative article included in the residual quantity group of the alternative articles is larger than the article adjusting quantity, determining that the residual quantity of the alternative articles which is larger than or equal to the article adjusting quantity does not exist in the residual quantity group of the alternative articles, and conducting descending processing on the residual quantity group of the alternative articles to obtain a residual quantity sequence of the alternative articles.
And step two, selecting the target number of the alternative article residual quantities from the alternative article residual quantity sequence in sequence. The sum of the residual amounts of the target number of the alternative articles is greater than or equal to the article blending amount, and the sum of the residual amounts of the alternative articles except the residual amount of the last alternative article in the residual amounts of the target number of the alternative articles is smaller than the article blending amount.
And thirdly, determining the initial article information corresponding to the residual amount of each candidate article in the target number of the residual amounts of the candidate articles as third article information to obtain the target number of the third article information.
And fourthly, performing association processing on each third item information in the target number of third item information and the shop mark included in the target item information to generate associated item information serving as alternative item information to obtain an alternative item information group. Here, the association process may refer to a splicing process.
Step 3046, updating each item information group according to the remaining quantity of each item corresponding to the at least one item candidate information, and performing the above processing steps again with each updated item information group as each item information group.
In some embodiments, the executing body may update each item information group according to a remaining amount of each item corresponding to the at least one item candidate information, and perform the processing step again with each updated item information group as each item information group.
In practice, according to the remaining quantity of each article corresponding to the at least one item candidate information, the executing body may update each item information group by:
first, for each item information item except the last item information item, the item information item corresponding to the item information item is updated by subtracting the remaining quantity of the item corresponding to the item information item from the quantity of the item included in the item information item corresponding to the item information item.
And secondly, determining the sum of the residual quantity of each article corresponding to each alternative article information except the last alternative article information in the at least one alternative article information as a first article adjustment quantity. In practice, first, the last item information candidate in the at least one item information candidate may be removed to update the at least one item information candidate. Then, the sum of the remaining quantity of each article corresponding to the updated at least one item candidate information may be determined as the first article adjustment quantity.
And thirdly, determining the difference value between the article adjustment amount and the first article adjustment amount as a second article adjustment amount.
And a fourth step of subtracting the second item adjustment amount from the number of items included in the item information in each item information group corresponding to the last item information in the at least one item information candidate, so as to update the item information corresponding to the last item information candidate.
The related content in step 304 serves as an inventive point of the present disclosure, thereby solving the technical problem mentioned in the background of the invention, namely "when the quantity of the purchased goods in a part of the stores is greater than the quantity required by the user, the overstock and the loss of the goods are caused". The factors that contribute to the backlog and wastage of articles tend to be as follows: when the quantity of the articles purchased by part of the shops is larger than the quantity required by the user, overstock and loss of the articles are caused. If the above factors are solved, the effects of reducing the overstock and the loss of the articles can be achieved. In order to achieve this effect, the present disclosure first removes item information whose store identifier included in each item information group is the same as the store identifier included in the target item information, and updates each item information group. Then, the item information satisfying the second scheduling condition is selected from the updated item information groups as initial item information, and an initial item information group is obtained. Wherein the second scheduling condition is: the item name included in the item information is the same as the item name included in the target item information. Therefore, stores with the quantity of articles purchased by part of stores larger than the quantity required by the user can be selected conveniently. Next, for each piece of initial article information in the initial article information group, a remaining article amount corresponding to the initial article information is generated based on the article flow amount, the article number, and the article prediction amount included in the initial article information. Therefore, the residual quantity of the articles in the shop corresponding to the target article information can be determined, and subsequent article scheduling is facilitated. Then, the remaining quantity of the articles larger than a preset threshold value is selected from the generated remaining quantities of the articles to be used as the remaining quantity of the alternative articles, and a group of the remaining quantity of the alternative articles is obtained. Therefore, the subsequent dispatching of the articles with large article residual quantity in the shop can be facilitated. And finally, generating at least one piece of alternative item information corresponding to the target item information according to the alternative item residual quantity group and the item adjustment quantity included by the target item information. Therefore, the articles with large article residual quantity in the shop can be conveniently dispatched to the alternative shop subsequently. Therefore, the inventory pressure when the quantity of the articles purchased by part of shops is larger than the quantity required by the user is relieved, and the overstock and the loss of the articles are reduced. And the excessive articles in the stores can be dispatched to the idle stores for circulation, so that the waste of space resources of the alternative stores is reduced.
And 305, controlling the related transfer robot to dispatch each article corresponding to the candidate article information group set according to each candidate shop corresponding to the target article information group set.
In some embodiments, the specific implementation of step 305 and the technical effect thereof may refer to step 205 in those embodiments corresponding to fig. 2, which are not described herein again.
As can be seen from fig. 3, compared with the description of some embodiments corresponding to fig. 2, the process 300 in some embodiments corresponding to fig. 3 relieves the inventory pressure when the quantity of the items purchased by some stores is greater than the demand of the user, and reduces the overstock and the loss of the items. And the excessive articles in the stores can be dispatched to the idle stores for circulation, so that the waste of space resources of the alternative stores is reduced.
With further reference to fig. 4, as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of an article scheduling apparatus, which correspond to those shown in fig. 2, and which may be applied in various electronic devices.
As shown in fig. 4, the article scheduling apparatus 400 of some embodiments includes: a first determination unit 401, a second determination unit 402, an acquisition unit 403, a third determination unit 404, and a control unit 405. Wherein the first determination unit 401 is configured to determine whether there is a store satisfying a first scheduling condition among stores in the target area in response to the current time being a scheduling time; the second determining unit 402 is configured to determine, in response to determining that there is a store, a store satisfying the first scheduling condition among the stores as an alternative store, resulting in an alternative store deck; the acquiring unit 403 is configured to acquire a target item information group corresponding to each candidate store in the candidate store set, and obtain a target item information group set; a third identifying unit 404 configured to identify a candidate item information group set corresponding to the target item information group set, based on each item information group corresponding to each store, wherein an item information group in each item information group corresponds to a store in each store; the control unit 405 is configured to control the associated transfer robot to dispatch each item corresponding to the candidate item information group set, based on each candidate store corresponding to the target item information group set.
It will be understood that the elements described in the apparatus 400 correspond to various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 400 and the units included therein, and will not be described herein again.
Referring now to FIG. 5, a block diagram of an electronic device (e.g., computing device 101 of FIG. 1) 500 suitable for use in implementing some embodiments of the present disclosure is shown. The electronic devices in some embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 5 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. 5, electronic device 500 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM) 502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are also stored. The processing device 501, the ROM502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and a communication device 509. The communication means 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data. While fig. 5 illustrates an electronic device 500 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. 5 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 via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program, when executed by the processing device 501, 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 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 electronic device; 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: determining whether stores meeting a first scheduling condition exist in stores in the target area in response to the current time being the scheduling time; in response to the determination of existence, determining the stores meeting the first scheduling condition in the stores as alternative stores to obtain alternative store pavements; acquiring a target article information group corresponding to each alternative shop in the alternative shop set to obtain a target article information group set; determining a candidate item information group set corresponding to the target item information group set according to each item information group corresponding to each store, wherein the item information group in each item information group corresponds to a store in each store; and controlling the related transfer robot to dispatch each article corresponding to the candidate article information group set according to each candidate shop corresponding to the target article information group 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 determining unit, a second determining unit, an obtaining unit, a third determining unit, and a control unit. The names of these units do not limit the units themselves in some cases, and for example, the control unit may be described as "a unit that controls the associated transfer robot to schedule each item corresponding to the candidate item information group set, based on each candidate store corresponding to the target item information group set".
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 (10)
1. An item scheduling method, comprising:
determining whether stores meeting a first scheduling condition exist in stores in the target area in response to the current time being the scheduling time;
in response to determining that the first scheduling condition exists, determining the stores meeting the first scheduling condition from the stores as alternative stores, and obtaining alternative store pavements;
acquiring a target article information group corresponding to each alternative shop in the alternative shop set to obtain a target article information group set;
determining a candidate article information group set corresponding to the target article information group set according to each article information group corresponding to each shop, wherein the article information group in each article information group corresponds to the shop in each shop;
and controlling the associated transfer robot to schedule each article corresponding to the candidate article information group set according to each candidate shop corresponding to the target article information group set.
2. The method according to claim 1, wherein the item information in each item information group includes a store identification, an item name, an item traffic amount corresponding to the item name, an item quantity, and an item forecast amount, and the target item information in the target item information group set includes a store identification, an item name, and an item adjustment amount; and
the determining, according to each item information group corresponding to each store, an alternative item information group set corresponding to the target item information group set includes:
for each target item information in the set of target item information groups, based on the respective item information group, performing the following processing steps:
removing the article information of which the shop identification included in each article information group is the same as the shop identification included in the target article information so as to update each article information group;
selecting article information meeting a second scheduling condition from the updated article information groups as initial article information to obtain an initial article information group, wherein the second scheduling condition is as follows: the article name included in the article information is the same as the article name included in the target article information;
for each initial article information in the initial article information group, generating an article residual amount corresponding to the initial article information based on an article flow amount, an article number and an article prediction amount included in the initial article information;
selecting the residual quantity of the articles larger than a preset threshold value from the generated residual quantities of the articles as the residual quantity of the alternative articles to obtain a group of the residual quantity of the alternative articles, wherein the preset threshold value is 0;
and generating at least one piece of alternative item information corresponding to the target item information according to the alternative item residual quantity group and the item adjustment quantity included by the target item information, wherein the at least one piece of alternative item information has an arrangement sequence.
3. The method of claim 2, wherein the method further comprises:
and updating each article information group according to the residual quantity of each article corresponding to the at least one piece of candidate article information, and executing the processing step again by taking each updated article information group as each article information group.
4. The method according to claim 2, wherein the generating at least one item candidate information corresponding to the target item information according to the item allocation amount included in the item candidate remaining amount group and the target item information comprises:
in response to the fact that the sum of the remaining quantities of all the alternative articles included in the group of the remaining quantities of the alternative articles is smaller than or equal to the article adjustment quantity, determining initial article information corresponding to the remaining quantity of each alternative article in the group of the remaining quantities of the alternative articles as first article information to obtain a first article information group;
and performing association processing on each first article information in the first article information group and the shop identifier included in the target article information to generate associated article information as alternative article information to obtain an alternative article information group.
5. The method according to claim 2, wherein the generating at least one item candidate information corresponding to the target item information according to the item allocation amount included in the item candidate remaining amount group and the target item information comprises:
in response to determining that the sum of the remaining quantities of the alternative items included in the group of remaining quantities of alternative items is greater than the item adjustment quantity, determining whether the remaining quantity of alternative items greater than or equal to the item adjustment quantity exists in the group of remaining quantities of alternative items;
in response to the fact that the alternative article residual quantity which is greater than or equal to the article adjusting quantity exists in the alternative article residual quantity group, determining the alternative article residual quantity which is greater than or equal to the article adjusting quantity in the alternative article residual quantity group as a first article residual quantity to obtain a first article residual quantity group;
determining initial article information corresponding to the first article residual quantity with the largest value in the first article residual quantity group as second article information;
and performing association processing on the second item information and the shop identification included in the target item information to generate associated item information as candidate item information.
6. The method according to claim 2, wherein the generating at least one item candidate information corresponding to the target item information according to the item allocation amount included in the item candidate remaining amount group and the target item information comprises:
in response to the fact that the sum of the remaining amount of each alternative item included in the alternative item remaining amount group is larger than the item adjustment amount, determining that the alternative item remaining amount which is larger than or equal to the item adjustment amount does not exist in the alternative item remaining amount group, performing descending processing on the alternative item remaining amount group, and obtaining an alternative item remaining amount sequence;
selecting a target number of alternative article residual quantities from the alternative article residual quantity sequence in sequence, wherein the sum of the target number of alternative article residual quantities is greater than or equal to the article adjustment quantity, and the sum of all alternative article residual quantities except the last alternative article residual quantity in the target number of alternative article residual quantities is less than the article adjustment quantity;
determining initial article information corresponding to the residual amount of each candidate article in the target number of candidate article residual amounts as third article information to obtain target number of third article information;
and associating each third item information in the target number of third item information with the shop mark included in the target item information to generate associated item information serving as alternative item information, so as to obtain an alternative item information group.
7. The method according to claim 3, wherein the updating of the respective item information groups according to the remaining amount of the respective items corresponding to the at least one candidate item information comprises:
for each alternative item information except the last alternative item information in the at least one alternative item information, subtracting the article residual quantity corresponding to the alternative item information from the article quantity included in the article information in each article information group corresponding to the alternative item information so as to update the article information corresponding to the alternative item information;
determining the sum of the residual quantity of each article corresponding to each alternative article information except the last alternative article information in the at least one alternative article information as a first article adjustment quantity;
determining a difference between the item adjustment amount and the first item adjustment amount as a second item adjustment amount;
and subtracting the second article adjustment amount from the article number included in the article information in each article information group corresponding to the last article information in the at least one article information candidate to update the article information corresponding to the last article information candidate.
8. An article scheduling apparatus comprising:
a first determination unit configured to determine whether there is a store satisfying a first scheduling condition among stores in the target area in response to a current time being a scheduling time;
a second determination unit configured to determine, in response to determination of presence, a store that satisfies the first scheduling condition among the stores as an alternative store, resulting in an alternative store deck;
an acquisition unit configured to acquire a target article information group corresponding to each of the candidate stores in the candidate store set, to obtain a target article information group set;
a third determining unit configured to determine, from each item information group corresponding to each store, an alternative item information group set corresponding to the target item information group set, wherein an item information group in each item information group corresponds to a store in the each store;
and the control unit is configured to control the related transfer robot to dispatch each article corresponding to the candidate article information group set according to each candidate shop corresponding to the target article information group 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.
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