CN111738651A

CN111738651A - Processing method, device and equipment for scheduling task

Info

Publication number: CN111738651A
Application number: CN202010424878.3A
Authority: CN
Inventors: 肖鹏宇
Original assignee: Beijing Jingdong Qianshi Technology Co Ltd
Current assignee: Beijing Jingdong Qianshi Technology Co Ltd
Priority date: 2020-05-19
Filing date: 2020-05-19
Publication date: 2020-10-02

Abstract

The embodiment of the invention provides a method, a device and equipment for processing a scheduling task, wherein the method comprises the following steps: determining a workstation set with scheduling requirements, and generating at least one scheduling task according to a warehouse returning inventory, a shelf inventory and an article warehouse-out requirement corresponding to each workstation in the workstation set; the type of each scheduling task is a first type or a second type; and in the at least one scheduling task, distributing the AGVs in the idle state to the scheduling tasks of the second type, and converting the AGVs corresponding to the scheduling tasks of the first type into the ex-warehouse state. In the embodiment, when the scheduling task is generated, not only the shelf inventory but also the warehouse returning inventory are considered, so that even if the shelf inventory cannot meet the goods warehouse-out requirements of some workstations, the workstations can be dispatched from the warehouse returning inventory, the workstations do not need to wait, and the goods warehouse-out efficiency is improved.

Description

Processing method, device and equipment for scheduling task

Technical Field

The embodiment of the invention relates to the field of warehouse logistics, in particular to a method, a device and equipment for processing scheduling tasks.

Background

With the development of warehouse logistics technology, various kinds of automation equipment are introduced into a warehouse operation environment to improve the warehouse operation efficiency and reduce the labor cost, so that a full-automatic or semi-automatic modern warehouse system is realized.

Modern warehousing systems include shelves and workstations, with a plurality of bins positioned on the shelves, each bin containing one or more items. When the goods need to be delivered from the warehouse, according to the goods delivery requirement, an Automatic Guided Vehicle (AGV) sequentially takes out a plurality of bins to a plurality of positions of the shelf and transports the bins to a workstation, and staff of the workstation picks the goods to be delivered from the bins. The sorted bins are then transported back to the rack by the AGV. In the prior art, when dispatching an ex-warehouse task, according to the article ex-warehouse requirement corresponding to each workstation, a plurality of material boxes capable of meeting the article ex-warehouse requirement are positioned on a shelf as much as possible, and then idle AGVs are dispatched to carry the positioned material boxes.

In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art: the efficiency of the goods delivery is low.

Disclosure of Invention

The embodiment of the invention provides a method, a device and equipment for processing a scheduling task, which are used for improving the delivery efficiency of articles.

In a first aspect, an embodiment of the present invention provides a method for processing a scheduling task, including:

determining a set of workstations having scheduling requirements;

generating at least one scheduling task according to the warehouse returning inventory, the shelf inventory and the article warehouse-out requirement corresponding to each workstation in the workstation set; the type of each scheduling task is a first type or a second type, the first type is used for indicating that one work station is subjected to ex-warehouse scheduling from the warehouse returning inventory, and the second type is used for indicating that one work station is subjected to ex-warehouse scheduling from the shelf inventory; the warehouse returning inventory is the inventory of an Automatic Guided Vehicle (AGV) in a warehouse returning state;

and in the at least one scheduling task, distributing the AGVs in the idle state to the scheduling tasks of the second type, and converting the AGVs corresponding to the scheduling tasks of the first type into the ex-warehouse state.

In a possible implementation manner, the generating at least one scheduling task according to the inventory of the warehouse, the inventory of the shelves, and the demand for the article to be delivered from the warehouse corresponding to each workstation in the workstation set includes:

repeatedly executing the scheduling step until the workstation set is empty, wherein the scheduling step comprises:

aiming at any first workstation in the workstation set, generating a candidate task corresponding to the first workstation according to the warehouse return inventory, the shelf inventory and the article warehouse-out requirement corresponding to the first workstation, and determining the score of the candidate task, wherein the score is used for indicating the matching degree between the candidate task and the article warehouse-out requirement of the first workstation;

determining the candidate task with the highest score as a scheduling task, determining the workstation corresponding to the candidate task with the highest score as a target workstation, and updating the warehouse-out requirement of the object workstation according to the candidate task with the highest score;

and if the target workstation does not have the scheduling requirement, deleting the target workstation from the workstation set.

In a possible implementation manner, the generating a candidate task corresponding to the first workstation according to the inventory of the returned items, the inventory of the shelves, and the demand for the items corresponding to the first workstation to be taken out of the warehouse, and determining a score of the candidate task includes:

generating a first candidate task corresponding to the first workstation according to the warehouse returning inventory and the goods delivery demand corresponding to the first workstation, and determining the score of the first candidate task, wherein the type of the first candidate task is the first type;

and generating a second candidate task corresponding to the first workstation according to the shelf inventory and the goods ex-warehouse demand corresponding to the first workstation, and determining the score of the second candidate task, wherein the type of the second candidate task is the second type.

In a possible implementation manner, the generating a first candidate task corresponding to the first workstation according to the backwarehouse inventory and the demand for delivering the item corresponding to the first workstation from the warehouse, and determining a score of the first candidate task includes:

acquiring a plurality of back-library AGVs in a back-library state and the inventory of each back-library AGV;

determining target AGVs from the multiple warehouse returning AGVs according to the matching degree between the inventory of each warehouse returning AGV and the article warehouse-out requirement corresponding to the first workstation;

and generating a first candidate task corresponding to the first workstation according to the target AGV, and determining the matching degree between the inventory of the target AGV and the article ex-warehouse demand corresponding to the first workstation as the score of the first candidate task.

In a possible implementation manner, each AGV for returning to the storage includes a plurality of bins, and each bin includes at least one article; according to the inventory of every AGV that returns storehouse with the degree of matching between the article demand that the storehouse is gone out that first workstation corresponds, follow determine target AGV from a plurality of AGV that return storehouse, include:

determining at least one candidate AGV from the plurality of back-to-back AGVs according to the article delivery requirement corresponding to the first workstation, wherein the number of bins, which can be provided for the first workstation, of the inventory of each candidate AGV is larger than or equal to a preset threshold value;

determining the matching degree of the inventory of the candidate AGV and the article delivery requirement corresponding to the first workstation according to the article type quantity which can be provided for the first workstation by each candidate AGV and the article quantity which can be provided for the first workstation;

and determining the candidate AGV corresponding to the maximum matching degree as the target AGV.

In one possible implementation manner, the generating a second candidate task corresponding to the first workstation according to the shelf inventory and the demand for delivering the item corresponding to the first workstation from the warehouse, and determining a score of the second candidate task includes:

determining a bin set which can be provided for the first workstation by the shelf stock according to the article delivery demand corresponding to the first workstation;

determining a target bin set from the bin sets, and determining a matching degree between the target bin set and an article delivery requirement corresponding to the first workstation according to the quantity of the articles which can be provided to the first workstation by the target bin set and the quantity of the articles which can be provided to the first workstation;

and generating a second candidate task corresponding to the first workstation according to the target work bin set, and determining the matching degree between the target work bin set and the article delivery requirement of the first workstation as the score of the second candidate task.

In one possible implementation, the determining a target bin set from the bin sets includes:

acquiring a first distance between a channel to which each bin in the bin set belongs and the first workstation, and taking the channel with the closest first distance as a first channel;

determining a second distance between the channel to which each bin in the bin collection belongs and the first channel;

sorting the bins in the bin set according to the sequence of the second distance from near to far;

and determining a target bin set from the bin sets according to the bin sequence in the sorted bin sets.

In a possible implementation manner, the number of the scheduling tasks of the second type is multiple, and each scheduling task of the second type includes a target bin set; the allocating the AGV in the idle state to the scheduling task of the second type includes:

for each scheduling task of the second type, determining the carrying sequence of each bin in the target bin set and a first bin in the carrying sequence according to the shortest carrying path;

and determining an AGV which is matched with each second type scheduling task from the AGVs in the idle state, so that the sum of the distances between the first bin which corresponds to each second type scheduling task and the matched AGV is minimum.

In one possible implementation, the determining a set of workstations with scheduling requirements includes:

and aiming at each preset workstation in a plurality of workstations, if the workstation has the requirement of delivering articles out of the warehouse and at least one idle parking space exists in the workstation, adding the workstation into the workstation set.

In a second aspect, an embodiment of the present invention provides a processing apparatus for scheduling tasks, including:

a determining module for determining a set of workstations having scheduling requirements;

the generating module is used for generating at least one scheduling task according to the warehouse returning inventory, the shelf inventory and the goods delivery demand corresponding to each workstation in the workstation set; the type of each scheduling task is a first type or a second type, the first type is used for indicating that one work station is subjected to ex-warehouse scheduling from the warehouse returning inventory, and the second type is used for indicating that one work station is subjected to ex-warehouse scheduling from the shelf inventory; the warehouse returning inventory is the inventory of an Automatic Guided Vehicle (AGV) in a warehouse returning state;

and the distribution module is used for distributing the AGVs in the idle state to the scheduling tasks of the second type in the at least one scheduling task and converting the AGVs corresponding to the scheduling tasks of the first type into the ex-warehouse state.

In a possible implementation manner, the generating module is specifically configured to:

In a possible implementation manner, each AGV for returning to the storage includes a plurality of bins, and each bin includes at least one article; the generation module is specifically configured to:

In a possible implementation manner, the number of the scheduling tasks of the second type is multiple, and each scheduling task of the second type includes a target bin set; the allocation module is specifically configured to:

In a possible implementation manner, the determining module is specifically configured to:

In a third aspect, an embodiment of the present invention provides an electronic device, including: a memory and a processor;

the memory is used for storing computer executable instructions, and the processor executes the computer executable instructions to implement the method according to any one of the first aspect.

In a fourth aspect, the present invention provides a computer-readable storage medium, in which computer-executable instructions are stored, and when executed by a processor, the computer-executable instructions are used to implement the method according to any one of the first aspect.

The embodiment of the invention provides a method, a device and equipment for processing a scheduling task, wherein the method comprises the following steps: determining a workstation set with scheduling requirements, and generating at least one scheduling task according to a warehouse returning inventory, a shelf inventory and an article warehouse-out requirement corresponding to each workstation in the workstation set; the type of each scheduling task is a first type or a second type, and in the at least one scheduling task, an AGV in an idle state is allocated to the scheduling task of the second type, and the AGV corresponding to the scheduling task of the first type is converted into an ex-warehouse state. In the embodiment, when the scheduling task is generated, not only the shelf inventory but also the warehouse returning inventory are considered, so that even if the shelf inventory cannot meet the goods warehouse-out requirements of some workstations, the workstations can be dispatched from the warehouse returning inventory, the workstations do not need to wait, and the goods warehouse-out efficiency is improved. In addition, when the warehouse returning inventory can meet the warehouse-out requirement of the work station, the warehouse returning inventory can be preferentially dispatched, namely, the warehouse returning inventory is directly converted into the warehouse-out inventory, so that the warehouse-out efficiency of the articles is further improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.

FIG. 1A is a schematic diagram of a possible application scenario in which embodiments of the present invention are applicable;

FIG. 1B is a block diagram of a possible system architecture according to an embodiment of the present invention;

fig. 2 is a flowchart illustrating a method for processing a scheduling task according to an embodiment of the present invention;

fig. 3 is a flowchart illustrating a method for processing a scheduling task according to another embodiment of the present invention;

fig. 4 is a schematic structural diagram of a processing apparatus for scheduling tasks according to an embodiment of the present invention;

fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention.

With the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.

The embodiment of the invention is suitable for the goods delivery scene of the warehousing system. The warehousing system can be a warehousing system in industries such as e-commerce, production, manufacturing and the like. For ease of understanding, an application scenario of the embodiment of the present invention is first described with reference to fig. 1A.

Fig. 1A is a schematic diagram of a possible application scenario to which the embodiment of the present invention is applied. As shown in FIG. 1A, the warehousing system includes a rack, a table and an AGV. Wherein, the goods shelves can be multilayer goods shelves, have placed the workbin on the goods shelves, and every workbin holding one or more article, the quantity of every article can be one or more. The workbench is used for picking the articles to be delivered out of the warehouse according to the orders. The AGV is used for transporting the bins on the shelves to the workstation for sorting, and the AGV can also be used for transporting the sorted bins back to the shelves. Where the AGV may be a multi-tiered bin AGV, such as in fig. 1A, the AGV may include multiple bin slots, and thus, the AGV may transport multiple bins at a time. It should be noted that the present embodiment is not limited to the number of bin levels included in the AGV.

For example, assuming that the articles to be delivered from a warehouse corresponding to a certain order are a cup, a hat and an earphone, when delivering from the warehouse, it is necessary to first locate in which bin or bins on the shelf the articles to be delivered from the warehouse are accommodated. It is assumed that the cups are housed in the bin 3, the caps are housed in the bin 5 and the earphones are housed in the bin 7. Next, as shown in FIG. 1A, bin 3, bin 5 and bin 7 are removed by the AGV in sequence to the corresponding location on the rack and transported to the workstation. From these bins, the cups, caps and earphones are picked up by the staff of the workstation. After the sorting is finished, the AGV transports the bin 3, the bin 5 and the bin 7 back to the corresponding positions of the shelf.

In practice, a warehousing system may include multiple racks, multiple workstations, and multiple AGVs. Therefore, the AGV needs to be reasonably scheduled according to the article warehouse-out requirements of each workbench so as to improve warehouse-out efficiency.

Fig. 1B is a schematic diagram of a possible system architecture according to an embodiment of the present invention. As shown in FIG. 1B, the system architecture includes a plurality of AGVs and a dispatching facility. The AGV and the dispatching equipment are in communication connection. And after the dispatching equipment generates the dispatching task, the dispatching task is issued to the AGV, so that the AGV is controlled to complete the warehouse-out transportation process or warehouse-back transportation process.

In the prior art, when a scheduling task is generated by scheduling equipment, a plurality of bins meeting the requirement of article delivery are positioned from a shelf as much as possible according to the requirement of article delivery corresponding to each workstation, and then idle AGVs corresponding to the region to which the work belongs are assigned to carry the positioned bins. However, in the process of implementing the present invention, the inventors found that the above prior art has at least the following problems: the efficiency of the goods delivery is low. The main aspects are one or more of the following: (1) for the goods delivery requirements of some workstations, the bins may not be positioned on the shelves temporarily, and the workstations are required to wait until the bins can be positioned on the shelves, so that the work stations are scheduled, and the goods delivery efficiency is low. (2) To some workstations, the distance between a plurality of workbins that fix a position on the goods shelves is far away or comparatively dispersed, and the distance that leads to AGV needs the transport is far away, and then leads to article warehouse-out inefficiency. (3) The material box and the AGV adopt a simple region responsible strategy, and each AGV is responsible for the material box delivery task in a certain region, so that the utilization of the AGV is not balanced, and the article delivery efficiency is reduced.

The processing method for scheduling tasks provided by the embodiment of the invention aims to solve at least one of the above technical problems in the prior art.

The following describes the technical solution of the present invention and how to solve the above technical problems with specific examples. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present invention will be described below with reference to the accompanying drawings.

Fig. 2 is a flowchart illustrating a processing method for scheduling tasks according to an embodiment of the present invention. The method of this embodiment may be performed by the scheduling apparatus in fig. 1B. As shown in fig. 2, the method of the present embodiment includes:

s201: a set of workstations having scheduling requirements is determined.

Wherein, the workstation set comprises one or more workstations with scheduling requirements. In this embodiment, a workstation having a scheduling requirement means that the workstation has an article warehouse-out requirement (for example, the workstation needs to warehouse out one or more articles), and the workstation satisfies the scheduled condition at the same time.

For example, in some application scenarios, a workstation is provided with multiple slots for parking the AGV. If all the parking spaces of one workstation are occupied, the workstation cannot park the newly scheduled AGV, and therefore the workstation does not meet the scheduled condition.

In one possible embodiment, for each of a plurality of workstations preset in the warehousing system, if the workstation satisfies the following conditions: and if the number of the idle parking spaces is larger than or equal to 1, adding the workstation into the workstation set.

S202: generating at least one scheduling task according to the warehouse returning inventory, the shelf inventory and the article warehouse-out requirement corresponding to each workstation in the workstation set; the type of each scheduling task is a first type or a second type, the first type is used for indicating that one work station is subjected to ex-warehouse scheduling from the warehouse returning inventory, and the second type is used for indicating that one work station is subjected to ex-warehouse scheduling from the shelf inventory.

In this embodiment, the backyard inventory refers to the inventory of AGVs in the backyard state. With reference to the application scenario shown in fig. 1A, after the work bench picks the bins, the AGV transports the picked bins back to the rack. On the way that the AGV is transported back to the shelf, the storage on the AGV (i.e., the storage in the sorted bin) is the warehouse-back storage. Shelf inventory refers to the inventory on a shelf, i.e., the inventory in the bin currently present on the shelf. Shelf inventory may also be referred to as in-store inventory. The goods delivery requirement corresponding to each workstation comprises the following steps: the kind of the goods which need to be delivered from the workstation, and the delivery quantity of each kind of goods.

In this embodiment, one or more scheduling tasks are generated according to the warehouse return inventory, the shelf inventory, and the article warehouse exit requirements corresponding to each workstation in the workstation set. And each scheduling task is used for performing ex-warehouse scheduling on one workstation. Specifically, for the warehouse-out requirement of the article corresponding to each workstation, warehouse-out scheduling can be performed on the workstation from the shelf inventory to generate a scheduling task, wherein the type of the scheduling task is a second type; the workstation can also be dispatched from the warehouse in the warehouse-returning inventory to generate a dispatching task, and the type of the dispatching task is the first type.

It should be understood that for a certain workstation, whether to select to perform outbound scheduling from shelf inventory or from backwarehouse inventory may adopt different strategies according to requirements, and this embodiment is not limited thereto. For example, the warehouse-out scheduling may be performed from shelf inventory preferentially, and when the shelf inventory cannot meet the demand, the warehouse-out scheduling may be performed from warehouse-back inventory. Or, the ex-warehouse scheduling can be preferentially selected from the ex-warehouse inventory, and when the ex-warehouse inventory cannot meet the requirement, the ex-warehouse scheduling is performed from the shelf inventory. Or, the two modes of warehouse-out scheduling from shelf inventory and warehouse-back inventory can be compared, and the mode with better scheduling efficiency is selected.

In addition, for a workstation, there may be zero, one, or more scheduling tasks. When there are multiple scheduling tasks corresponding to a certain workstation, the types of the multiple scheduling tasks may be the same or different, that is, all of the scheduling tasks may be of a first type, all of the scheduling tasks may be of a second type, or a part of the scheduling tasks may be of the first type and another part of the scheduling tasks may be of the second type.

In this embodiment, S202 may have various embodiments, and will be briefly described below with reference to two possible embodiments.

In one possible implementation, the traversal may be performed for each workstation in the set of workstations, and for each workstation, the outbound scheduling may be performed from either backwarehouse inventory or from shelf inventory. For example, firstly, a scheduling task corresponding to the workstation 1 is generated according to the warehouse-back inventory and the shelf inventory; and then generating a scheduling task corresponding to the workstation 2 according to the warehouse returning inventory and the shelf inventory, and so on. In the embodiment, the article ex-warehouse demand of the workstation which is traversed firstly can be ensured to be met preferentially.

In another possible implementation manner, the scheduling task with the optimal scheduling efficiency may be generated each time according to the warehouse-back inventory, the shelf inventory and the article warehouse-out demand corresponding to each workstation in the workstation set. Specifically, the following scheduling steps (1) to (3) are repeatedly performed until the set of workstations is empty.

(1) And aiming at any first workstation in the workstation set, generating a candidate task corresponding to the first workstation according to the warehouse returning inventory, the shelf inventory and the article warehouse-out requirement corresponding to the first workstation, and determining the score of the candidate task, wherein the score is used for indicating the matching degree between the candidate task and the article warehouse-out requirement of the first workstation. It can be understood that the score of each scheduling task may be used to measure the scheduling efficiency corresponding to the scheduling task, that is, the higher the matching degree is, the higher the scheduling efficiency is.

(2) Determining the candidate task with the highest score as a scheduling task, determining the workstation corresponding to the candidate task with the highest score as a target workstation, and updating the warehouse-out requirement of the object workstation according to the candidate task with the highest score.

(3) And if the target workstation does not have the scheduling requirement, deleting the target workstation from the workstation set. For example, if the target workstation does not have any scheduling requirement (e.g., does not have an item ex-warehouse requirement or does not satisfy the scheduled condition) after the scheduling task is scheduled, the target workstation is deleted from the workstation set.

In the implementation mode, the scheduling sequence is not arranged among the workstations, the workstations are considered in a comprehensive mode in each round, and the scheduling tasks generated in each round are guaranteed to be optimal in scheduling efficiency, so that the goods delivery efficiency can be improved on the whole.

S203: and in the at least one scheduling task, distributing the AGVs in the idle state to the scheduling tasks of the second type, and converting the AGVs corresponding to the scheduling tasks of the first type into the ex-warehouse state.

In this embodiment, after generating at least one scheduling task, for the scheduling task of the first type, only the corresponding AGV needs to be converted into the out-of-library state. For a second type of scheduled task, an AGV in an idle state is allocated. Furthermore, the scheduling tasks can be issued to the corresponding AGVs, so that the AGVs execute the scheduling tasks, thereby completing the outbound requirement of each workstation in the workstation set.

The method for processing the scheduling task provided by the embodiment includes: determining a workstation set with scheduling requirements, and generating at least one scheduling task according to a warehouse returning inventory, a shelf inventory and an article warehouse-out requirement corresponding to each workstation in the workstation set; the type of each scheduling task is a first type or a second type, and in the at least one scheduling task, an AGV in an idle state is allocated to the scheduling task of the second type, and the AGV corresponding to the scheduling task of the first type is converted into an ex-warehouse state. In the embodiment, when the scheduling task is generated, not only the shelf inventory but also the warehouse returning inventory are considered, so that even if the shelf inventory cannot meet the goods warehouse-out requirements of some workstations, the workstations can be dispatched from the warehouse returning inventory, the workstations do not need to wait, and the goods warehouse-out efficiency is improved. In addition, when the warehouse returning inventory can meet the warehouse-out requirement of the work station, the warehouse returning inventory can be preferentially dispatched, namely, the warehouse returning inventory is directly converted into the warehouse-out inventory, so that the warehouse-out efficiency of the articles is further improved.

Fig. 3 is a flowchart illustrating a method for processing a scheduling task according to another embodiment of the present invention. This embodiment further refines the embodiment shown in fig. 2. As shown in fig. 3, the method of the present embodiment includes:

s301: a set of workstations having scheduling requirements is determined.

The method of this embodiment may be triggered at regular time, for example, may be triggered to execute every half minute, and generate one or more scheduling tasks each time execution is performed.

In order to ensure the scheduling accuracy and the scheduling efficiency, before S301, an additional operation with the same work station may be performed on the article delivery requirement of each work station, that is, each work station performs additional positioning of the article to be delivered in the bin which has been scheduled before but has not been sorted back to the bin, so that no delivery bin and delivery scheduling task are newly added.

In this embodiment, for convenience of description, the number of remaining free parking spaces of the workstation w is recorded as H_wMarking the article warehouse-out requirement corresponding to the workstation w as X_wI.e. X_w＝{(s，q_s) Where s denotes an item to be delivered, q_sIndicating the number of outgoing items corresponding to the item type s. The set of workstations with scheduling requirements is denoted as W.

In S301, all workstations in the warehousing system can be traversed, and corresponding H with the article delivery requirement is obtained_wWorkstations > 0 are added to the set of workstations W.

S302: determining whether the set of workstations is empty.

If yes, go to step S307. If not, executing S303 to S306 in a circulating way until the workstation set is empty. Wherein, S303 is to generate a candidate task corresponding to each workstation according to the stock-returning, and S304 is to generate a candidate task corresponding to each workstation according to the shelf stock. S305 is to select an optimal candidate task from the plurality of candidate tasks as a scheduling task.

For convenience of description, in this embodiment, the candidate tasks generated in S303 and S304 are added to the candidate task set Ω. Each execution round, the initialization candidate task set Ω is empty, i.e.

S303: and aiming at any first workstation in the workstation set, generating a first candidate task corresponding to the first workstation according to the warehouse return inventory and the goods warehouse-out requirement corresponding to the first workstation, and determining the score of the first candidate task.

Specifically, a plurality of library returning AGVs in a library returning state and an inventory of each library returning AGV may be acquired. And then, according to the matching degree between the inventory of each back-warehouse AGV and the article delivery requirement corresponding to the first workstation, determining a target AGV from the multiple back-warehouse AGVs. It should be appreciated that the target AGV is a return AGV that may provide bins to the first workstation.

Optionally, the target AGV may be determined in the following feasible manner: aiming at each first workstation w, according to the article warehouse-out requirement X corresponding to the first workstation w_wAt least one candidate AGV is determined from the plurality of AGVs, and the number of bins of each candidate AGV available to the first workstation w in stock is greater than or equal to a preset threshold. For example: according to the goods delivery requirement X of the first workstation w_wChecking the number of bins which can be provided for the first workstation w by all the warehouse returning AGVs, and determining the warehouse returning AGVs of which the number of available bins is greater than or equal to a preset threshold value as candidate AGVs, wherein the preset threshold value can be α A_N，α∈[0，1]To configure the parameters, A_NThe maximum number of bins that can be simultaneously handled at one time for each AGV.

Then, according to the quantity of the types of articles which can be provided for the first workstation w by each candidate AGV and the quantity of the articles which can be provided for the first workstation w, determining the matching degree between the inventory of the candidate AGV and the article delivery requirement corresponding to the first workstation w; and determining the candidate AGV corresponding to the maximum matching degree as the target AGV. For example, for the ith candidate AGV, the item delivery requirement X of the ith candidate AGV and the first workstation w can be calculated according to the following formula_wDegree of match therebetween

And selecting a degree of matching

The highest candidate AGV is taken as the target AGV.

Wherein β is the balance weight,

the number of types of items available to the first workstation w for the ith candidate AGV,

the number of items available to the first workstation w for the ith candidate AGV.

And then, according to the target AGV, generating a first candidate task corresponding to the first workstation w, and matching the inventory of the target AGV with the goods delivery requirements corresponding to the first workstation w

A score is determined for the first candidate task. Illustratively, the target AGV, the degree of matching

The corresponding available bin set and the corresponding first workstation w are added to the candidate task set omega.

In this embodiment, when the first candidate task is generated for the first workstation w, the inventory of each warehouse returning AGV and the item warehouse-out requirement X of the first workstation w are considered_wThe matching degree between the first working station w and the second working station w can be selected to be matched with the matching degree between the first working station w and the second working station w, and therefore the goods delivery efficiency can be improved.

S304: and aiming at any first workstation in the workstation set, generating a second candidate task corresponding to the first workstation according to shelf inventory and an article ex-warehouse demand corresponding to the first workstation, and determining the score of the second candidate task.

In particular, the method comprises the following steps of,according to the goods delivery demand corresponding to the first workstation w, the bin set K which can be provided for the first workstation by the shelf stock can be determined_w. Gathering K from the bin_wTo determine a target bin set I_wIt is to be understood that the target bin set I_wGathering for work bin K_wA subset of, a target bin set I_wIs a group of bins that may be handled by an AGV.

Alternatively, the target bin set I may be determined in a manner that is feasible_w: obtaining a bin set K_wA first distance between the lane to which each bin in (a) belongs and the first workstation w, and taking the lane closest to the first distance as the first lane; determining a bin set K_wA second distance between the channel to which each bin belongs and the first channel; collecting the workbins K according to the sequence of the second distance from near to far_wSorting the bins; gathering K from the bins in the order of the sorted bins_wTo determine a target bin set I_w。

For example, gathering K from bins in sequence in the order of sorted bins_wTaking out one bin and adding the bin into a target bin set I_wUntil the delivery of the articles from the first work station w is fulfilled, or until the bin collection K is completed_wEmpty, or, up to the target bin set I_wHas reached the maximum single transportable bin number A of a single AGV_N. It should be noted that, in the slave bin group K_wAdding selected material box into target material box set I_wIn the process, if the article in the current bin to be selected is not needed by the first workstation w, namely the previously selected bin meets the article requirement, the current bin to be selected is skipped and is not added into the target bin set I_w。

Then, collecting I according to the target bin_wThe number of article types available to the first station w, and the number of articles available to the first station w, determine the target bin set I_wThe goods delivery demand X corresponding to the first workstation w_wThe degree of match between them. For example, the following formula can be used to calculateTarget bin set I_wThe goods delivery demand X corresponding to the first workstation w_wDegree of match therebetween

Wherein β is the balance weight,

for a target bin set I_wThe number of article types available to the first station w in the middlebox,

for a target bin set I_wThe number of articles in the intermediate bin available to the first station w.

Further, according to the target bin set I_wGenerating a second candidate task corresponding to the first workstation w, and collecting the target workbin set I_wWith the goods delivery requirement X of the first workstation w_wDegree of match therebetween

A score for the second candidate task is determined. Illustratively, the target bin is collected I_wDegree of matching

And adding the corresponding first workstation w into the candidate task set omega.

In this embodiment, the target bin set I is considered when generating the second candidate task for the first workstation w_wThe matching degree with the goods delivery requirement of the first workstation w can be preferentially selected, so that the target bin set I with high matching degree can be preferentially selected_wAnd (4) carrying out ex-warehouse scheduling on the first workstation w, thereby improving the ex-warehouse efficiency of the articles. In addition, in determining the target bin set I_wWhen considering the passage of the bin andthe distance between the first work stations w and the distance between the lanes of different bins is such that the bins closer together may be preferentially selected for adding to the target bin set I_wTherefore, the carrying distance of the AGV can be reduced, and the article delivery efficiency is further improved.

S305: and determining the candidate task with the highest score as a scheduling task and determining the workstation corresponding to the candidate task with the highest score as a target workstation in a plurality of candidate tasks corresponding to the workstation set.

Illustratively, the candidate task with the highest score is selected from the candidate task set Ω as the scheduling task generated in the current round. It can be appreciated that the scheduled tasks generated in this round may be of the first type or the second type.

And if the scheduling task generated in the current round is of the first type, directly returning to the library and transferring out of the library. If the scheduling task generated in the current round is of the second type, one idle AGV needs to be occupied, and therefore the number A of the idle AGVs is updated, namely A is equal to A-1.

Further, when the scheduling task generated in the current round is of a second type, the target bin set I can be determined according to the shortest carrying path_wThe order of the handling of the bins, and the first bin in the order of handling. It should be understood that, when determining the carrying order, the carrying order may be determined by solving a Travelling Salesman Problem (TSP), and may also be determined by traversing all possible fetching box orders, which is not limited in this embodiment.

In this embodiment, when each round of scheduling tasks is generated, the work stations are considered as a whole, and it is ensured that the scheduling efficiency of each round of generated scheduling tasks is optimal, so that the efficiency of delivering articles out of the warehouse can be improved as a whole.

S306: and updating the goods delivery requirement corresponding to the target workstation, and deleting the target workstation from the workstation set if the target workstation does not have the scheduling requirement.

Specifically, the goods delivery requirement X corresponding to the target workstation_wUpdating to determine the target task after the current round of scheduling taskAnd making the corresponding goods delivery requirement of the station. Furthermore, since the scheduling task generated in the current round needs to occupy one free parking space of the target workstation, the number H of the free parking spaces of the target workstation is also needed_wAnd (6) updating.

After the update, if the target workstation does not have a scheduling requirement (e.g., no free space or no item out-of-warehouse requirement), the target workstation is deleted from the set of workstations W. In addition, if there is no candidate task for a certain workstation in the candidate task set Ω generated in the current round, it indicates that neither the warehouse return inventory nor the shelf inventory can meet the demand for the work station to leave the warehouse (i.e. the work station cannot be located to the bin), and the work station is deleted from the work station set W.

S307: and in the generated at least one scheduling task, distributing the AGV in an idle state to the scheduling task of the second type, and converting the AGV corresponding to the scheduling task of the first type into an ex-warehouse state.

Specifically, for each second type of scheduling task, the conveying order of the bins in the target bin set and the first bin in the conveying order may be determined according to the shortest conveying path. Then, from the AGVs in the idle state, an AGV matching with each second type scheduling task is determined, so that the sum of the distances between the first bin corresponding to each second type scheduling task and the corresponding AGV is minimum.

For example, assuming that a set corresponding to the second type of scheduling task (i.e., the scheduling task to be allocated with the idle AGVs) is denoted as N, and a set of all current idle AGVs is denoted as M, a matching relationship between the second type of scheduling task and the idle AGVs may be determined by solving the following objective function.

An objective function:

wherein x is_mn1 denotes that the mth idle AGV is selected to execute the scheduling task n, L_mnIndicating the distance between the mth idle AGV and the first bin of the scheduled task n.

The following constraints are required for solving the objective function. The meaning of the constraint (1) is: for each scheduling task n, a maximum of 1 free AGV is matched. The meaning of the constraint (2) is: for each free AGV, it performs a maximum of 1 scheduling task. The meaning of the constraint (3) is: x is the number of_mnThe value of (1) is 0 or 1, that is, the mth idle AGV executes the scheduling task n, or the mth idle AGV does not execute the scheduling task n.

It should be understood that the above objective function is globally scheduled when the scheduling task and the idle AGVs are matched, so that optimal scheduling is ensured and the problem of unbalanced AGVs utilization is avoided.

In the embodiment, when the scheduling task is generated, not only the shelf inventory but also the warehouse returning inventory are considered, so that even if the shelf inventory cannot meet the goods warehouse-out requirements of some workstations, the workstations can be dispatched from the warehouse returning inventory, the workstations do not need to wait, and the goods warehouse-out efficiency is improved. And when each round of scheduling task is generated, all the workstations are considered in a comprehensive mode, and the scheduling task generated in each round is guaranteed to be optimal in scheduling efficiency, so that the goods delivery efficiency can be improved integrally. Because the shortest carrying distance of the AGV is ensured when the scheduling task is generated and the idle AGV is matched for the scheduling task, the warehouse-out efficiency of the articles can be further improved. When the idle AGVs are matched for the scheduling task, overall scheduling is carried out, so that optimal scheduling is guaranteed, and the problem of unbalanced utilization of the AGVs is avoided.

Fig. 4 is a schematic structural diagram of a processing device for scheduling tasks according to an embodiment of the present invention. The apparatus provided in this embodiment may be in the form of software and/or hardware. As shown in fig. 4, the processing device 10 for scheduling tasks according to the present embodiment includes: a determination module 11, a generation module 12 and an assignment module 13.

The determining module 11 is configured to determine a set of workstations having scheduling requirements;

the generating module 12 is configured to generate at least one scheduling task according to the warehouse return inventory, the shelf inventory, and the article warehouse exit demand corresponding to each workstation in the workstation set; the type of each scheduling task is a first type or a second type, the first type is used for indicating that one work station is subjected to ex-warehouse scheduling from the warehouse returning inventory, and the second type is used for indicating that one work station is subjected to ex-warehouse scheduling from the shelf inventory; the warehouse returning inventory is the inventory of an Automatic Guided Vehicle (AGV) in a warehouse returning state;

and the allocating module 13 is configured to allocate an AGV in an idle state to the scheduling task of the second type in the at least one scheduling task, and convert the AGV corresponding to the scheduling task of the first type into an out-of-warehouse state.

In a possible implementation manner, the generating module 12 is specifically configured to:

In a possible implementation manner, each AGV for returning to the storage includes a plurality of bins, and each bin includes at least one article; the generating module 12 is specifically configured to:

In a possible implementation manner, the number of the scheduling tasks of the second type is multiple, and each scheduling task of the second type includes a target bin set; the allocation module 13 is specifically configured to:

In a possible implementation manner, the determining module 11 is specifically configured to:

The processing apparatus for scheduling tasks provided in this embodiment may be configured to execute the technical solution of any of the above method embodiments, and the implementation principle and the technical effect are similar, which are not described herein again.

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. The electronic device may act as a scheduling device. As shown in fig. 5, the electronic device 20 of the present embodiment includes: a processor 21 and a memory 22; a memory 22 for storing a computer program; the processor 21 is configured to execute the computer program stored in the memory to implement the processing method of the scheduling task in the above embodiments. Reference may be made in particular to the description relating to the method embodiments described above.

Alternatively, the memory 22 may be separate or integrated with the processor 21.

When the memory 22 is a device independent from the processor 21, the electronic device 20 may further include: a bus 23 for connecting the memory 22 and the processor 21.

Optionally, the electronic device 20 may also include a communication component 24 for communicating with the AGVs.

The electronic device provided in this embodiment may be configured to execute the technical solution in any of the method embodiments, and the implementation principle and the technical effect are similar, which are not described herein again.

An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a computer program, and the computer program is used to implement the technical solutions in any of the above method embodiments.

An embodiment of the present invention further provides a chip, including: the system comprises a memory, a processor and a computer program, wherein the computer program is stored in the memory, and the processor runs the computer program to execute the technical scheme of any one of the method embodiments.

In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described device embodiments are merely illustrative, and for example, the division of the modules is only one logical division, and other divisions may be realized in practice, for example, a plurality of modules may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or modules, and may be in an electrical, mechanical or other form.

The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.

In addition, functional modules in the embodiments of the present invention may be integrated into one processing unit, or each module may exist alone physically, or two or more modules are integrated into one unit. The unit formed by the modules can be realized in a hardware form, and can also be realized in a form of hardware and a software functional unit.

The integrated module implemented in the form of a software functional module may be stored in a computer-readable storage medium. The software functional module is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention.

It should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in the incorporated application may be directly implemented by a hardware processor, or may be implemented by a combination of hardware and software modules in the processor.

The memory may comprise a high-speed RAM memory, and may further comprise a non-volatile storage NVM, such as at least one disk memory, and may also be a usb disk, a removable hard disk, a read-only memory, a magnetic or optical disk, etc.

The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (EISA) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, the buses in the figures of the present invention are not limited to only one bus or one type of bus.

The storage medium may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disks. A storage media may be any available media that can be accessed by a general purpose or special purpose computer.

An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be integral to the processor. The processor and the storage medium may reside in an Application Specific Integrated Circuits (ASIC). Of course, the processor and the storage medium may reside as discrete components in an electronic device or host device.

Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.

Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.

It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A processing method for scheduling tasks, comprising:

determining a set of workstations having scheduling requirements;

generating at least one scheduling task according to the warehouse returning inventory, the shelf inventory and the article warehouse-out requirement corresponding to each workstation in the workstation set; the type of each scheduling task is a first type or a second type, the first type is used for indicating that one work station is subjected to ex-warehouse scheduling from the warehouse returning inventory, and the second type is used for indicating that one work station is subjected to ex-warehouse scheduling from the shelf inventory; the warehouse returning inventory is the inventory of the automatic guide transport vehicle in the warehouse returning state;

and in the at least one scheduling task, allocating the automatic guided vehicle in the idle state to the scheduling task of the second type, and converting the automatic guided vehicle corresponding to the scheduling task of the first type into a delivery state.

2. The method of claim 1, wherein generating at least one scheduling task based on the inventory returned, the shelf inventory, and the demand for the items to be removed from the warehouse for each workstation in the set of workstations comprises:

3. The method of claim 2, wherein generating a candidate task for the first workstation and determining a score for the candidate task based on the backwarehouse inventory, the shelf inventory, and the demand for the item for the first workstation to be taken out of the warehouse comprises:

4. The method according to claim 3, wherein the generating a first candidate task corresponding to the first workstation according to the backwarehouse inventory and the outbound demand of the item corresponding to the first workstation, and determining the score of the first candidate task comprises:

acquiring a plurality of warehouse returning automatic guiding transport vehicles in a warehouse returning state and the inventory of each warehouse returning automatic guiding transport vehicle;

determining a target automatic guided transport vehicle from the plurality of warehouse returning automatic guided transport vehicles according to the matching degree between the inventory of each warehouse returning automatic guided transport vehicle and the article warehouse-out requirement corresponding to the first workstation;

and generating a first candidate task corresponding to the first workstation according to the target automatic guided transport vehicle, and determining the matching degree between the inventory of the target automatic guided transport vehicle and the goods delivery demand corresponding to the first workstation as the score of the first candidate task.

5. The method of claim 4, wherein each of the plurality of returnable automated guided vehicles includes a plurality of bins in inventory, each bin including at least one item therein; the determining a target automated guided vehicle from the plurality of warehouse returning automated guided vehicles according to the matching degree between the inventory of each warehouse returning automated guided vehicle and the article warehouse-out requirement corresponding to the first workstation comprises:

according to the goods delivery requirement corresponding to the first workstation, at least one candidate automatic guided vehicle is determined from the plurality of automatic guided vehicles returning to the warehouse, and the number of bins, which can be provided for the first workstation, of the inventory of each candidate automatic guided vehicle is larger than or equal to a preset threshold value;

determining the matching degree of the inventory of each candidate automatic guided transport vehicle and the delivery demand of the items corresponding to the first workstation according to the quantity of the types of the items which can be provided for the first workstation by each candidate automatic guided transport vehicle and the quantity of the items which can be provided for the first workstation;

and determining the candidate automatic guided vehicle corresponding to the maximum matching degree as the target automatic guided vehicle.

6. The method of claim 3, wherein generating a second candidate assignment for the first workstation based on the shelf inventory and the demand for the item corresponding to the first workstation to be taken out of the warehouse and determining a score for the second candidate assignment comprises:

7. The method of claim 6, wherein the determining a target bin set from the bin sets comprises:

8. The method according to any one of claims 1 to 7, wherein the number of the scheduled tasks of the second type is plural, each scheduled task of the second type comprising a target bin set; the assigning of the automated guided vehicle in an idle state to the scheduled tasks of the second type comprises:

and determining the matched automatic guided vehicle for each second type of scheduling task from the automatic guided vehicles in the idle state, so that the sum of the distances between the first bin corresponding to each second type of scheduling tasks and the matched automatic guided vehicle is minimum.

9. The method of any of claims 1 to 7, wherein determining the set of workstations that have scheduling requirements comprises:

10. A processing apparatus that schedules tasks, comprising:

the generating module is used for generating at least one scheduling task according to the warehouse returning inventory, the shelf inventory and the goods delivery demand corresponding to each workstation in the workstation set; the type of each scheduling task is a first type or a second type, the first type is used for indicating that one work station is subjected to ex-warehouse scheduling from the warehouse returning inventory, and the second type is used for indicating that one work station is subjected to ex-warehouse scheduling from the shelf inventory; the warehouse returning inventory is the inventory of the automatic guide transport vehicle in the warehouse returning state;

and the distribution module is used for distributing the automatic guided vehicle in the idle state to the scheduling task of the second type in the at least one scheduling task and converting the automatic guided vehicle corresponding to the scheduling task of the first type into the delivery state.

11. An electronic device, comprising: a memory and a processor;

the memory is used for storing computer-executable instructions, and the processor executes the computer-executable instructions to implement the method of any one of claims 1 to 9.

12. A computer-readable storage medium having computer-executable instructions stored thereon, which when executed by a processor, are configured to implement the method of any one of claims 1 to 9.