CN113450049B - Method, device and storage medium for determining ex-warehouse site - Google Patents
Method, device and storage medium for determining ex-warehouse site Download PDFInfo
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Abstract
The invention provides a method, a device and a storage medium for determining a delivery site, wherein the method comprises the following steps: acquiring a carrier set and a delivery site set in a working area, wherein the carrier set comprises one or more carriers, and the delivery site set comprises one or more delivery sites; determining the position relation between each carrier and each ex-warehouse station, and establishing a network flow model by taking the carrier and the ex-warehouse station as nodes and determining the cost between the nodes according to the position relation; and solving a minimum cost maximum flow problem according to the network flow model, and determining the delivery station of each carrier. According to the technical scheme, all the trucks in the working area and the delivery stations are combined, the delivery station of each truck is determined by considering the whole, and the delivery efficiency can be improved.
Description
Technical Field
The invention relates to the technical field of warehouse management, in particular to a method and a device for determining a warehouse-out site and a storage medium.
Background
Along with the continuous development of technology, warehouse management is usually carried out through a warehouse management system (Warehouse MANAGEMENT SYSTEM, WMS) at present, and when the warehouse management system manages goods to go out of warehouse, goods transportation devices such as fork trucks and the like are scheduled to travel to the side of a goods shelf through an algorithm, after the goods are received, the goods are carried to a warehouse-out site, and the goods are put into a conveyor belt which is in butt joint with the warehouse-out site to finish warehouse-out operation. Wherein, the selection of the delivery site directly affects delivery efficiency.
At present, a greedy algorithm or a random algorithm is often adopted to determine a delivery site, and most of delivery problems of a single forklift are only considered, but the method can cause too many forklifts selecting the same delivery site for delivery, so that congestion is caused, and delivery efficiency of goods is affected.
Disclosure of Invention
The invention solves the problem of how to improve the efficiency of goods delivery.
In order to solve the problems, the invention provides a method and a device for determining a delivery site and a storage medium.
In a first aspect, the present invention provides a method for determining a delivery site, including:
Acquiring a carrier set and a delivery site set in a working area, wherein the carrier set comprises one or more carriers, and the delivery site set comprises one or more delivery sites;
determining the position relation between each carrier and each ex-warehouse station, and establishing a network flow model by taking the carrier and the ex-warehouse station as nodes and determining the cost between the nodes according to the position relation;
and solving a minimum cost maximum flow problem according to the network flow model, and determining the delivery station of each carrier.
Optionally, the working area includes a plurality of sub-areas, and the determining a positional relationship between each of the trucks and each of the delivery sites includes:
acquiring a first position where each carrier is located and a second position where each delivery station is located;
for each truck, determining whether the truck and each delivery station are in the same subarea according to the first position and the second position;
And determining a distance between the truck and each of the delivery sites according to the first position and the second position.
Optionally, the network flow model includes a source point, a plurality of first nodes, a plurality of second nodes and a sink point, the establishing the network flow model includes:
Taking the carrier as the first node, and taking the warehouse-out site as a second site;
and establishing a directed edge between the source point and each first node, establishing a directed edge between each first node and each second node, and establishing a directed edge between each second node and the sink point, wherein the cost of the directed edge between the first node and the second node is related to the position relationship between the first node and the second node.
Optionally, the cost of the directed edge between the first node and the second node is represented by a first formula comprising:
C(i,j)＝α·A+β·S,
Wherein C (i, j) is a cost of a directed edge between the ith first node and the jth second node, α is a preset first parameter, β is a preset second parameter, and a=0 when the ith first node and the jth second node are in the same sub-area; a=1 when the i-th and j-th first nodes are not in the same sub-region; s is the distance between the ith first node and the jth second node.
Optionally, the upper limit of the flow of the directed edge between the source point and each first node is 1, and the cost is 0; the upper limit of the flow between each first node and each second node is 1; for any second node, the upper limit of the traffic of the directed edge between the second node and the sink is the upper limit of the station busyness of the second node, the lower limit of the traffic is a preset threshold, and the cost is 0.
Optionally, after solving the minimum-cost maximum-flow problem according to the network flow model, the method further includes:
and determining the site busyness upper limit of the directed edges of each second node and the sink by adopting a dichotomy, so that when the flow of the directed edges of the second nodes and the sink is equal to the site busyness upper limit, the maximum flow of the network flow model is equal to the number of the transport vehicles, and the total cost of the network flow model is minimum.
Optionally, the carrier moves unidirectionally in the working area, the ex-warehouse station and the warehouse-in station are paired in pairs, and for any one of the ex-warehouse station, the warehouse-in station corresponding to the ex-warehouse station is the warehouse-in station which is located in the moving direction of the carrier and is closest to the ex-warehouse station;
and the lower limit of the flow of the directed edge between the second node and the sink is the ratio of the corresponding goods to be put in the put-in station to the maximum goods carrying capacity of each carrier.
In a second aspect, the present invention provides a delivery site determining apparatus, including:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring a carrier set and a storage station set in a working area, the carrier set comprises one or more carriers, and the storage station set comprises one or more storage stations;
The model building module is used for determining the position relation between each carrier and each ex-warehouse station, determining the cost between the nodes by taking the carrier and the ex-warehouse station as nodes according to the position relation, and building a network flow model;
and the processing module is used for solving the minimum cost maximum flow problem according to the network flow model and determining the delivery station of each carrier.
In a third aspect, the present invention provides an electronic device comprising a memory and a processor;
The memory is used for storing a computer program;
The processor is configured to implement the ex-warehouse site determination method as described above when executing the computer program.
In a fourth aspect, the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a delivery site determining method as described above.
The method and the device for determining the delivery site and the storage medium have the beneficial effects that: determining the position relation between each carrier and each ex-warehouse station in the working area, determining the cost among the nodes according to the position relation, combining all the carriers with all the ex-warehouse stations, and establishing a network flow model. Solving the minimum cost maximum flow problem for the network flow model, and determining the delivery site of each carrier. According to the technical scheme, all the trucks and all the delivery stations in the working area are considered integrally, the delivery stations of all the trucks are determined, congestion at the delivery stations caused by setting the delivery stations for each truck can be avoided, and the delivery efficiency is improved.
Drawings
FIG. 1 is a flow chart of a method for determining a delivery site according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a network flow model according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a delivery site determining apparatus according to an embodiment of the present invention.
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the invention described herein may be implemented in sequences other than those illustrated or otherwise described herein.
The work area may include a warehouse, a workshop, etc., and in the following, the warehouse is often divided into a plurality of sub-areas, for example, to facilitate management of goods, etc: dividing subareas according to the types of stored cargoes, wherein the area where the mobile phone is located is one subarea, and the subarea where the computer is located is another subarea. The sub-areas are generally crossed in connectivity, and if the carrier performs cross-region operation, the efficiency is low, so that cross-region delivery tasks are not generated as much as possible when the delivery sites of the carriers are determined.
Each sub-area is provided with a plurality of shelves, the warehouse further comprises one or more warehouse-in stations, one or more warehouse-out stations and a conveyor belt, the conveyor belt is in butt joint with the warehouse-out stations and is used for conveying cargoes to the rear end for packing or ex-warehouse, the trucks move in one direction in the warehouse, the warehouse-out stations and the warehouse-in stations are paired in pairs, and for any warehouse-out station, the warehouse-in station corresponding to the warehouse-out station is the warehouse-in station which is located in the moving direction of the trucks and has the nearest distance with the warehouse-out station.
The carrier can include AGV, AMR, fork truck and robot etc. when the carrier received shipment task, remove by the goods shelves, and on the device such as accessible manipulator selected the carrier, the goods generally prevented on the tray or in the workbin, the carrier carried the goods to the delivery site, placed on with delivery site docking conveyer belt or other handling equipment, accomplished delivery operation. Then, the carrier is moved to a warehouse-in station corresponding to the warehouse-out station along the fixed moving direction, and the goods at the warehouse-in station are carried to the goods shelf.
As shown in fig. 1, the method for determining a delivery site according to the embodiment of the present invention may be performed by an electronic device (e.g., a server) in a warehouse system, and the method includes:
Step S110, a truck set and a delivery site set in a work area are obtained, wherein the truck set comprises one or more trucks, and the delivery site set comprises one or more delivery sites.
And step S120, determining the position relation between each carrier and each ex-warehouse station, and establishing a network flow model by taking the carrier and the ex-warehouse station as nodes and determining the cost among the nodes according to the position relation.
Specifically, the positional relationship between the truck and the delivery site includes whether the truck and the delivery site are in the same sub-area, and the distance between the truck and the delivery site.
Optionally, the working area includes a plurality of sub-areas, and the determining a positional relationship between each of the trucks and each of the delivery sites includes:
acquiring a first position where each carrier is located and a second position where each delivery station is located;
For each truck, determining whether the truck and each delivery station are in the same subarea according to the first position and the second position.
Specifically, when the truck and the delivery site are in the same subregion, it means that the truck does not need to perform the cross-region operation when the delivery operation is performed, and conversely, when the truck and the delivery site are not in the same subregion, it means that the truck needs to perform the cross-region operation when the delivery operation is performed.
And determining a distance between the truck and each of the delivery sites according to the first position and the second position.
Optionally, the network flow model includes a source point, a plurality of first nodes, a plurality of second nodes and a sink point, the establishing the network flow model includes:
Taking the carrier as the first node, and taking the warehouse-out site as a second site;
and establishing a directed edge between the source point and each first node, establishing a directed edge between each first node and each second node, and establishing a directed edge between each second node and the sink point, wherein the cost of the directed edge between the first node and the second node is related to the position relationship between the first node and the second node.
Specifically, as shown in fig. 2, S is a source point, T is a sink point, robot is a first node, that is, a carrier, robot1 is a first carrier, robot2 is a second carrier, and so on, n carriers are total, where n is greater than or equal to 1; the station is a second node, namely a delivery station, the station1 is a first delivery station, the station2 is a second delivery station, and the like, and m delivery stations are all provided, wherein m is greater than or equal to 1. The cost of the directed edge between the first node and the second node is related to whether the first node and the second node are in the same sub-region or not, and is positively related to the distance between the first node and the second node.
A directional edge is respectively arranged between the source point S and the robot1 and the robot2 … … robotn, the directional edge is respectively arranged between the robot1 and the station1 and between the robot2 and the station2 … … stationm, the directional edge is respectively arranged between the robot2 and the station1 and between the robot2 and the station2 … … stationm, and the like, the directional edge is respectively arranged from the source point S to the first node to the second node. And a directed edge is respectively arranged between the station1 and the station2 … … stationm and between the station2 and the sink T, and points to the sink T from the second node.
In this optional embodiment, all the trucks in the warehouse are combined with the delivery site to establish a network flow model, so that the delivery site of each truck can be subjected to system optimization, the condition that the delivery site is selected independently for the truck, and the congestion at the delivery site is avoided, and the delivery efficiency can be improved.
Optionally, the cost of the directed edge between the first node and the second node is represented by a first formula comprising:
C(i,j)＝α·A+β·S,
Wherein C (i, j) is a cost of a directed edge between the ith first node and the jth second node, α is a preset first parameter, β is a preset second parameter, and a=0 when the ith first node and the jth second node are in the same sub-area; a=1 when the i-th and j-th first nodes are not in the same sub-region; s is the distance between the ith first node and the jth second node.
Specifically, because the connectivity between subareas in the warehouse is poorer than the connectivity in the subareas, the efficiency of the carrier in the cross-region operation is lower, and the carrier is required to carry out cross-region delivery when the carrier and the delivery site are not in the same subarea, so that at the moment, A=1 has higher cost, and alpha is a parameter for measuring the influence of the cross-region delivery on the efficiency; when the carrier and the delivery site are in the same subarea, the carrier does not need to continue to deliver the warehouse in a cross-region way, so that at the moment, A=0, the influence of the cross-region on the efficiency is avoided, and the cost of the cross-region is not calculated. When the delivery objects of the carrier are delivered out of the warehouse, obviously, the closer the distance between the delivery objects and the warehouse-out site is, the higher the warehouse-out efficiency of the goods is, the cost of reflecting the directed edge between the second node and the sink is positively related to the distance, and beta is a parameter for measuring the influence of the distance between the carrier and the warehouse-out site on the efficiency.
In this optional embodiment, the cost of the directed edge between the first node and the second node is related to the distribution situation of each sub-area of the delivery site in the warehouse, so that when the delivery site is selected subsequently, the selection of the delivery site crossing the area can be avoided, the delivery of the warehouse in a cross-area manner can be avoided as much as possible, and the delivery efficiency is further improved.
Optionally, the upper limit of the flow of the directed edge between the source point and each first node is 1, and the cost is 0; the upper limit of the flow between each first node and each second node is 1; for any second node, the upper limit of the traffic of the directed edge between the second node and the sink is the upper limit of the station busyness of the second node, the lower limit of the traffic is a preset threshold, and the cost is 0. Wherein the preset threshold may be pre-stored in the electronic device.
Specifically, the upper limit of the flow of the directed edge between the delivery site and the sink may be set according to the delivery capacity of each delivery site, for example, assuming that one delivery site can process the goods transported by U vehicles at the same time, that is, the upper limit of the site busyness of the delivery site is U, and the upper limit of the flow of the corresponding directed edge is set as U.
In this optional embodiment, the upper limit of the flow of the directed edge between the second node and the sink is the upper limit of the busyness of the site corresponding to the delivery site, and when the delivery site of each carrier is determined, the total flow of each delivery site cannot exceed the upper limit of the busyness of the site, so that the carrier is prevented from being jammed, and the delivery efficiency is prevented from being affected.
Optionally, the preset threshold corresponding to the directed edge between the second node and the sink is a ratio between the corresponding amount of the goods to be put in the warehouse at the warehouse-in site and the maximum load capacity of each carrier.
Specifically, as the carrier moves unidirectionally in the warehouse, after the goods are placed on the conveyor belt which is in butt joint with the ex-warehouse station, the goods at the ex-warehouse station are moved to the warehouse-warehouse station corresponding to the ex-warehouse station, warehouse-in operation is carried out on the goods at the warehouse-in station, and the total of Z boxes of goods to be warehouse-in is provided, and the maximum carrying capacity of each carrier is K boxes, all the goods can be warehouse-in only by at least Z/K carriers, so that the lower limit of the flow of the directional edge between the second node and the sink is Z/K.
In this optional embodiment, the lower limit of the flow of the directed edge between the second node and the sink is set to be the number of the carriers required for the goods warehouse entry of the corresponding warehouse entry site, and the connection of warehouse entry and exit services is considered, so that all the goods can be ensured to finish warehouse entry operation, and the efficiency between warehouse entry and warehouse exit can be improved.
Optionally, after solving the minimum-cost maximum-flow problem according to the network flow model, the method further includes:
and determining the site busyness upper limit of the directed edges of each second node and the sink by adopting a dichotomy, so that when the flow of the directed edges of the second nodes and the sink is equal to the site busyness upper limit, the maximum flow of the network flow model is equal to the number of the transport vehicles, and the total cost of the network flow model is minimum.
Specifically, when the maximum flow of the network flow model is equal to the number n of carriers, indicating that all of the carriers have corresponding outbound sites, assuming a directional edge between the first sites roboti and stationj has a feasible flow, the outbound site of the carrier roboti is set to stationj.
And step S130, solving a minimum cost maximum flow problem according to the network flow model, and determining the delivery sites of the vehicles.
Specifically, according to the network flow model, the minimum cost maximum flow problem can be solved by adopting the existing algorithms such as Bellman-Ford algorism (Bellman-Ford algorithm), and the like, and the specific solving process is the prior art and is not repeated here. Solving the minimum cost maximum flow problem on the network flow model, and setting ex-warehouse stations for more trucks as much as possible to obtain a result, wherein the closer ex-warehouse stations are selected as much as possible, each truck does not cross-region ex-warehouse as much as possible, and the number of the trucks of each ex-warehouse station is ensured to be larger than or equal to the number required by the corresponding warehouse-in station and smaller than or equal to the maximum number of the trucks which can be received by the ex-warehouse station.
In this embodiment, the location relationship between each truck and each ex-warehouse station in the working area is determined, the cost between the nodes is determined according to the location relationship, and all the trucks and all the ex-warehouse stations are combined to establish the network flow model. Solving the minimum cost maximum flow problem for the network flow model, and determining the delivery site of each carrier. According to the technical scheme, all the trucks and all the delivery stations in the working area are considered integrally, the delivery stations of all the trucks are determined, congestion at the delivery stations caused by setting the delivery stations for each truck can be avoided, and the delivery efficiency is improved.
As shown in fig. 3, a device for determining a delivery site provided by an embodiment of the present invention includes:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring a carrier set and a storage station set in a working area, the carrier set comprises one or more carriers, and the storage station set comprises one or more storage stations;
The model building module is used for determining the position relation between each carrier and each ex-warehouse station, determining the cost between the nodes by taking the carrier and the ex-warehouse station as nodes according to the position relation, and building a network flow model;
and the processing module is used for solving the minimum cost maximum flow problem according to the network flow model and determining the delivery station of each carrier.
An electronic device provided in another embodiment of the present invention includes a memory and a processor; the memory is used for storing a computer program; the processor is configured to implement the ex-warehouse site determination method as described above when executing the computer program. The electronic device may be a computer or a server, etc.
A further embodiment of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the ex-warehouse site determination method as described above.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in accordance with the embodiments may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed may comprise the steps of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random-access Memory (Random Access Memory, RAM), or the like. In the present application, the units described as separate units may or may not be physically separate, and units displayed as units 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 units may be selected according to actual needs to achieve the purpose of the embodiment of the present application. In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
Although the present disclosure is disclosed above, the scope of the present disclosure is not limited thereto. Various changes and modifications may be made by one skilled in the art without departing from the spirit and scope of the disclosure, and these changes and modifications will fall within the scope of the disclosure.
Claims (10)
1. A method for determining a delivery site, comprising:
Acquiring a carrier set and a delivery site set in a working area, wherein the carrier set comprises one or more carriers, and the delivery site set comprises one or more delivery sites;
Determining the position relation between each carrier and each ex-warehouse station, and establishing a network flow model by taking the carrier and the ex-warehouse station as nodes and determining the cost between the nodes according to the position relation, wherein the position relation comprises whether the carrier and the ex-warehouse station are in the same subarea or not and the distance between the carrier and the ex-warehouse station, and the upper limit of the flow of a directed edge between the ex-warehouse station and the sink of the network flow model is set according to the ex-warehouse capacity of each ex-warehouse station;
and solving a minimum cost maximum flow problem according to the network flow model, and determining the delivery station of each carrier.
2. The method of claim 1, wherein the work area includes a plurality of sub-areas, and the determining a positional relationship between each of the vehicles and each of the delivery sites includes:
acquiring a first position where each carrier is located and a second position where each delivery station is located;
for each truck, determining whether the truck and each delivery station are in the same subarea according to the first position and the second position;
And determining a distance between the truck and each of the delivery sites according to the first position and the second position.
3. The method according to claim 1 or 2, wherein the network flow model includes a source point, a plurality of first nodes, a plurality of second nodes, and a sink point, the determining costs between nodes based on the positional relationship with the carrier and the outbound site as nodes, and the establishing the network flow model includes:
Taking the carrier as the first node, and taking the warehouse-out site as a second site;
and establishing a directed edge between the source point and each first node, establishing a directed edge between each first node and each second node, and establishing a directed edge between each second node and the sink point, wherein the cost of the directed edge between the first node and the second node is related to the position relationship between the first node and the second node.
4. The method of claim 3, wherein the cost of the directed edge between the first node and the second node is represented by a first formula comprising:
C(i,j)＝α·A+β·S,
Wherein C (i, j) is a cost of a directed edge between the ith first node and the jth second node, α is a preset first parameter, β is a preset second parameter, and a=0 when the ith first node and the jth second node are in the same sub-area; a=1 when the i-th first node and the j-th second node are not in the same sub-area; s is the distance between the ith first node and the jth second node.
5. The method for determining a delivery site according to claim 3, wherein the upper limit of the flow of the directed edge between the source point and each first node is 1, and the cost is 0; the upper limit of the flow between each first node and each second node is 1; for any second node, the upper limit of the traffic of the directed edge between the second node and the sink is the upper limit of the station busyness of the second node, the lower limit of the traffic is a preset threshold, and the cost is 0.
6. The method according to claim 5, wherein after solving the minimum-cost maximum-flow problem according to the network flow model, further comprising:
and determining the site busyness upper limit of the directed edges of each second node and the sink by adopting a dichotomy, so that when the flow of the directed edges of the second nodes and the sink is equal to the site busyness upper limit, the maximum flow of the network flow model is equal to the number of the transport vehicles, and the total cost of the network flow model is minimum.
7. The ex-warehouse station determining method according to claim 5, wherein the carrier moves in one direction in the work area, the ex-warehouse station and the in-warehouse station are paired in pairs, and for any of the ex-warehouse stations, the in-warehouse station corresponding to the ex-warehouse station is the in-warehouse station located in the moving direction of the carrier and closest to the ex-warehouse station;
and the lower limit of the flow of the directed edge between the second node and the sink is the ratio of the corresponding goods to be put in the put-in station to the maximum goods carrying capacity of each carrier.
8. A delivery site determining apparatus, comprising:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring a carrier set and a storage station set in a working area, the carrier set comprises one or more carriers, and the storage station set comprises one or more storage stations;
The model building module is used for determining the position relation between each carrier and each ex-warehouse site, taking the carrier and the ex-warehouse site as nodes, and determining the cost between the nodes according to the position relation, and building a network flow model, wherein the position relation comprises whether the carrier and the ex-warehouse site are in the same subarea or not and the distance between the carrier and the ex-warehouse site, and the upper limit of the flow of the directed edge between the outlet-warehouse site and the sink of the network flow model is set according to the ex-warehouse capacity of each ex-warehouse site;
and the processing module is used for solving the minimum cost maximum flow problem according to the network flow model and determining the delivery station of each carrier.
9. An electronic device comprising a memory and a processor;
The memory is used for storing a computer program;
the processor for implementing the ex-warehouse site determination method as claimed in any one of claims 1 to 7 when executing the computer program.
10. A computer readable storage medium, characterized in that the storage medium has stored thereon a computer program which, when executed by a processor, implements the ex-warehouse site determination method according to any one of claims 1 to 7.
Priority Applications (1)
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