CN113450049A - Exit site determining method and device and storage medium - Google Patents
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Abstract
The invention provides a method, a device and a storage medium for determining a warehouse-out site, wherein the method comprises the following steps: acquiring a carrier set and an ex-warehouse station set in a work area, wherein the carrier set comprises one or more carriers, and the ex-warehouse station set comprises one or more ex-warehouse stations; determining the position relationship between each transport vehicle and each ex-warehouse site, determining the cost between nodes according to the position relationship by taking the transport vehicle and the ex-warehouse site as nodes, and establishing a network flow model; solving a minimum cost maximum flow problem according to the network flow model, and determining the ex-warehouse station of each truck. According to the technical scheme, all the carrying vehicles in the working area and the delivery stations are combined, the delivery stations of all the carrying vehicles are determined by taking the whole consideration, and the delivery efficiency can be improved.
Description
Technical Field
The invention relates to the technical field of warehousing management, in particular to a method and a device for determining ex-warehouse stations and a storage medium.
Background
With the continuous development of science and technology, Warehouse Management is usually performed through a Warehouse Management System (WMS), the Warehouse Management System manages goods to be delivered from a Warehouse, the goods transportation devices such as a forklift are dispatched to the side of a goods shelf through an algorithm, after the goods are received, the goods are transported to a delivery station, and the goods are placed on a conveyor belt butted with the delivery station to complete delivery. Wherein, the selection of the ex-warehouse site directly influences the ex-warehouse efficiency.
At present, a greedy algorithm or a random algorithm is often adopted to determine a delivery station, and most of all the delivery problems of a single forklift are considered, but the method may cause too many forklifts to select the same delivery station for delivery, so that congestion is caused, and the delivery efficiency of goods is influenced.
Disclosure of Invention
The invention solves the problem of how to improve the efficiency of goods delivery.
In order to solve the above problems, the present invention provides a method, an apparatus, and a storage medium for determining a delivery site.
In a first aspect, the present invention provides a method for determining a delivery site, including:
acquiring a carrier set and an ex-warehouse station set in a work area, wherein the carrier set comprises one or more carriers, and the ex-warehouse station set comprises one or more ex-warehouse stations;
determining the position relationship between each transport vehicle and each ex-warehouse site, determining the cost between nodes according to the position relationship by taking the transport vehicle and the ex-warehouse site as nodes, and establishing a network flow model;
solving a minimum cost maximum flow problem according to the network flow model, and determining the ex-warehouse station of each truck.
Optionally, the work area comprises a plurality of sub-areas, and the determining the positional relationship between each of the trucks and each of the delivery stations comprises:
acquiring a first position of each carrier and a second position of each delivery station;
for each of the trucks, determining from the first and second positions whether the truck is in the same sub-area as the respective outbound site;
and determining the distance between the truck and each delivery station 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, and the determining, with the truck and the delivery site as nodes, a cost between the nodes according to the location relationship includes:
taking the transport vehicle as the first node, and taking the delivery station as a second station;
establishing a directed edge between the source node 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, 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, the first formula including:
C(i,j)＝α·A+β·S,
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 when the ith first node and the jth second node are in the same sub-region, a is 0; when the ith first node and the jth second node are not in the same sub-region, a is 1; s is the distance between the ith first node and the jth second node.
Optionally, the upper flow limit of the directed edge between the source point and each first node is 1, and the cost is 0; the upper flow limit between each first node and each second node is 1; for any second node, the upper flow limit 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 flow limit is a preset threshold, and the cost is 0.
Optionally, after the solving the minimum cost maximum flow problem according to the network flow model, the method further includes:
and determining the station busyness upper limit of each directed edge of the second node and the sink by adopting a bisection method, so that when the flow of the directed edges of the second node and the sink is equal to the station busyness upper limit, the maximum flow of the network flow model is equal to the number of the carriers, and the total cost of the network flow model is minimum.
Optionally, the truck moves in the working area in a unidirectional manner, the delivery station and the warehousing station are paired pairwise, and for any delivery station, the warehousing station corresponding to the delivery station is the warehousing station which is located in the moving direction of the truck and has the closest distance to the delivery station;
the lower flow limit of the directed edge between the second node and the sink is the ratio of the amount of the goods to be warehoused at the corresponding warehousing site to the maximum cargo carrying capacity of each carrier.
In a second aspect, the present invention provides an ex-warehouse site determining apparatus, including:
an acquisition module to acquire a set of vehicles in a work area and a set of ex-warehouse sites, the set of vehicles including one or more vehicles, the set of ex-warehouse sites including one or more ex-warehouse sites;
the model building module is used for determining the position relationship between each transport vehicle and each ex-warehouse site, determining the cost between the nodes according to the position relationship by taking the transport vehicles and the ex-warehouse sites as the nodes, and building a network flow model;
and the processing module is used for solving the problem of minimum cost and maximum flow according to the network flow model and determining the ex-warehouse station of each carrier.
In a third aspect, the present invention provides an electronic device comprising a memory and a processor;
the memory for storing a computer program;
the processor is configured to implement the outbound 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 the ex-warehouse site determination method as described above.
The beneficial effects of the ex-warehouse site determining method, the ex-warehouse site determining device and the storage medium are as follows: and determining the position relation between each transport vehicle and each ex-warehouse site in the working area, determining the cost among the nodes according to the position relation, and combining all transport vehicles and all ex-warehouse sites to establish a network flow model. Solving the problem of minimum cost and maximum flow for the network flow model, and determining the ex-warehouse station of each carrier. According to the technical scheme, all the carrying vehicles and all the delivery stations in the working area are considered integrally, the delivery stations of all the carrying vehicles are determined, congestion at the delivery stations caused by independently setting the delivery stations for each carrying vehicle can be avoided, and delivery efficiency is improved.
Drawings
Fig. 1 is a schematic flow chart of a ex-warehouse site determination method 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 to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein.
The work area may include areas such as warehouses, workshops, etc., and the warehouses are taken as examples below, and are often divided into a plurality of sub-areas for the convenience of managing goods, etc., for example: and dividing sub-regions according to the types of stored goods, wherein the region where the mobile phone is located is one sub-region, and the region where the computer is located is the other sub-region. Since the sub-areas are usually communicated with each other and the efficiency of the carrier is low when the carrier performs the cross-area operation, the cross-area delivery task is not generated as much as possible when the delivery station of each carrier is determined.
The warehouse comprises a plurality of sub-areas, and is characterized in that a plurality of shelves are arranged in each sub-area, the warehouse also comprises one or more warehousing stations, one or more ex-warehouse stations and a conveyor belt, the conveyor belt is in butt joint with the ex-warehouse stations and is used for conveying goods to the rear end for packaging or ex-warehouse, the carrier moves in the warehouse in one direction, the ex-warehouse stations and the warehousing stations are paired in pairs, and for any ex-warehouse station, the warehousing station corresponding to the ex-warehouse station is the warehousing station which is located in the moving direction of the carrier and has the closest distance to the ex-warehouse station.
The carrier can include AGV, AMR, fork truck and robot etc. and when the carrier received the shipment task, moved to by goods shelves, accessible manipulator etc. selected the goods to the carrier on, the goods usually prevents on the tray or in the workbin, and the carrier is with goods transport to the delivery site, places on the conveyer belt or other haulage equipment with delivery site butt joint, accomplishes the operation of delivering from godown. Then, the carrier moves in the fixed moving direction to the warehousing site corresponding to the ex-warehousing site, and carries the goods at the warehousing site to the shelf.
As shown in fig. 1, an embodiment of the present invention provides a method for determining a warehouse-out site, where the method is executed by an electronic device (e.g., a server) in a warehousing system, and the method includes:
step S110, a carrier set and a delivery station set in a working area are obtained, wherein the carrier set comprises one or more carriers, and the delivery station set comprises one or more delivery stations.
And step S120, determining the position relationship between each transport vehicle and each ex-warehouse site, determining the cost between nodes according to the position relationship by taking the transport vehicle and the ex-warehouse site as nodes, and establishing a network flow model.
Specifically, the positional relationship between the transportation vehicle and the delivery station includes whether the transportation vehicle and the delivery station are in the same sub-area, and the distance between the transportation vehicle and the delivery station.
Optionally, the work area comprises a plurality of sub-areas, and the determining the positional relationship between each of the trucks and each of the delivery stations comprises:
acquiring a first position of each carrier and a second position of each delivery station;
for each of the vehicles, determining whether the vehicle is in the same sub-area as the respective delivery station based on the first and second locations.
Specifically, when the carrier and the delivery station are in the same sub-area, indicating that the delivery operation is performed, the carrier does not need to perform the transregional operation, and conversely, when the carrier and the delivery station are not in the same sub-area, indicating that the delivery operation is performed, the carrier needs to perform the transregional operation.
And determining the distance between the truck and each delivery station 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, and the determining, with the truck and the delivery site as nodes, a cost between the nodes according to the location relationship includes:
taking the transport vehicle as the first node, and taking the delivery station as a second station;
establishing a directed edge between the source node 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, 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 in fig. 2 is a source, T is a sink, robot is a first node, i.e., a truck, robot1 is a first truck, robot2 is a second truck, and so on, there are n trucks, where n is greater than or equal to 1; the station is the second node, namely the ex-warehouse station, the station1 is the first ex-warehouse station, the station2 is the second ex-warehouse station, and so on, there are m ex-warehouse stations, and 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.
There is a directed edge between the source point S and the robot1, robot2 … … robotn, respectively, pointing to the first node from the source point S, there is a directed edge between the robot1 and the station1, station2 … …, respectively, there is a directed edge between the robot2 and the station1, station2 … …, respectively, and so on, pointing to the second node from the first node. There is a directed edge between the station1, station2 … … station and the sink T, respectively, pointing from the second node to the sink T.
In this optional embodiment, all the carriers in the warehouse and the ex-warehouse stations are combined to establish a network flow model, so that system optimization can be performed on the ex-warehouse stations of the carriers, congestion at the ex-warehouse stations caused by selection of the ex-warehouse stations for the carriers alone is avoided, and ex-warehouse 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, the first formula including:
C(i,j)＝α·A+β·S,
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 when the ith first node and the jth second node are in the same sub-region, a is 0; when the ith first node and the jth second node are not in the same sub-region, a is 1; s is the distance between the ith first node and the jth second node.
Specifically, because the connectivity between sub-areas in the warehouse is poorer than the connectivity inside the sub-areas, the efficiency is lower when the vehicles cross-area work, and when the vehicles and the ex-warehouse stations are not in the same sub-area, it indicates that the vehicles need to cross-area ex-warehouse, therefore, at this time, a is 1, the cost is higher, and α is a parameter for measuring the influence of cross-area ex-warehouse on the efficiency; when the carrier and the delivery site are in the same sub-area, the carrier does not need to continue to be delivered from the warehouse in a cross-area mode, therefore, at the moment, A is equal to 0, the influence of the cross-area on the efficiency is avoided, and the cost of the cross-area is not calculated. When the transport vehicle transports goods to be delivered from the warehouse, obviously, the closer the distance between the transport vehicle and the warehouse delivery station is, the higher the warehouse delivery efficiency of the goods is, the cost of the directed edge reflected between the second node and the sink is in positive correlation with the distance, and beta is a parameter for measuring the influence of the distance between the transport vehicle and the warehouse delivery station 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 of the ex-warehouse sites in each sub-area of the warehouse, so that when the ex-warehouse sites are subsequently selected, the selection of cross-area ex-warehouse sites can be avoided, cross-area ex-warehouse can be avoided as much as possible, and the ex-warehouse efficiency can be further improved.
Optionally, the upper flow limit of the directed edge between the source point and each first node is 1, and the cost is 0; the upper flow limit between each first node and each second node is 1; for any second node, the upper flow limit 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 flow limit 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 rate 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, if one delivery site can process goods conveyed by U carriers at the same time, that is, the upper limit of the station busyness of the delivery site is U, and the upper limit of the flow rate of the corresponding directed edge is 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 station busyness of the corresponding delivery station, and when the delivery station of each carrier is determined, the total flow of each delivery station cannot exceed the upper limit of the station busyness, so that the carrier congestion is avoided, 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 amount of goods to be warehoused at the corresponding warehousing site and the maximum cargo carrying capacity of each truck.
Specifically, the carriers move unidirectionally in the warehouse, the goods are placed on the conveying belt butted with the delivery site and then move to the warehousing site corresponding to the delivery site, warehousing operation is performed on the goods at the warehousing site, assuming that all goods needing to be warehoused are boxed, Z boxes of goods to be warehoused are needed totally, and the maximum transportation amount of each carrier is K boxes, all goods can be warehoused only by at least Z/K carriers, so the lower flow limit of the directed 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 the number of the carriers required for warehousing the goods corresponding to the warehousing site, and the linking of warehousing and ex-warehousing services is considered, so that it can be ensured that all goods complete warehousing operations, and the efficiency between warehousing and ex-warehousing can be improved.
Optionally, after the solving the minimum cost maximum flow problem according to the network flow model, the method further includes:
and determining the station busyness upper limit of each directed edge of the second node and the sink by adopting a bisection method, so that when the flow of the directed edges of the second node and the sink is equal to the station busyness upper limit, the maximum flow of the network flow model is equal to the number of the carriers, 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 the vehicles, it indicates that all the vehicles have corresponding ex-warehouse stations, and assuming that a feasible flow exists on a directed edge between the first station roboti and the stationj, the ex-warehouse station of the vehicle roboti is set to the stationj.
Step S130, solving a minimum cost maximum flow problem according to the network flow model, and determining the ex-warehouse station of each truck.
Specifically, according to the network flow model, the minimum cost maximum flow problem can be solved by using the existing algorithms such as Bellman-Ford algorithm (Bellman-Ford algorithm), and the specific solving process is the prior art and is not described herein again. Solving the problem of minimum cost and maximum flow for the network flow model, and setting the delivery stations for more carriers as much as possible according to the obtained result, wherein the more recent delivery stations are selected as much as possible, each carrier is prevented from being delivered from a cross area as much as possible, and the number of the carriers of each delivery station is larger than or equal to the number required by the corresponding storage station and is smaller than or equal to the maximum number of the carriers capable of being received by the delivery station.
In this embodiment, the position relationship between each transport vehicle and each ex-warehouse site in the working area is determined, the cost between the nodes is determined according to the position relationship, and all transport vehicles and all ex-warehouse sites are combined to establish a network flow model. Solving the problem of minimum cost and maximum flow for the network flow model, and determining the ex-warehouse station of each carrier. According to the technical scheme, all the carrying vehicles and all the delivery stations in the working area are considered integrally, the delivery stations of all the carrying vehicles are determined, congestion at the delivery stations caused by independently setting the delivery stations for each carrying vehicle can be avoided, and delivery efficiency is improved.
As shown in fig. 3, an ex-warehouse site determining apparatus provided in an embodiment of the present invention includes:
an acquisition module to acquire a set of vehicles in a work area and a set of ex-warehouse sites, the set of vehicles including one or more vehicles, the set of ex-warehouse sites including one or more ex-warehouse sites;
the model building module is used for determining the position relationship between each transport vehicle and each ex-warehouse site, determining the cost between the nodes according to the position relationship by taking the transport vehicles and the ex-warehouse sites as the nodes, and building a network flow model;
and the processing module is used for solving the problem of minimum cost and maximum flow according to the network flow model and determining the ex-warehouse station of each carrier.
Another embodiment of the present invention provides an electronic device comprising a memory and a processor; the memory for storing a computer program; the processor is configured to implement the outbound 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 outbound site determining method as described above.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes 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 (RAM), or the like. In this application, the units described as separate parts may or may not be physically separate, and parts 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 can be selected according to actual needs to achieve the purpose of the solution of the embodiment of the present invention. In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
Although the present disclosure has been described above, the scope of the present disclosure is not limited thereto. Various changes and modifications may be effected therein by one of ordinary skill in the pertinent art without departing from the spirit and scope of the present disclosure, and these changes and modifications are intended to be within the scope of the present disclosure.
Claims (10)
1. A method for determining a warehouse-out site, comprising:
acquiring a carrier set and an ex-warehouse station set in a work area, wherein the carrier set comprises one or more carriers, and the ex-warehouse station set comprises one or more ex-warehouse stations;
determining the position relationship between each transport vehicle and each ex-warehouse site, determining the cost between nodes according to the position relationship by taking the transport vehicle and the ex-warehouse site as nodes, and establishing a network flow model;
solving a minimum cost maximum flow problem according to the network flow model, and determining the ex-warehouse station of each truck.
2. The method according to claim 1, wherein the work area includes a plurality of sub-areas, and the determining the positional relationship between each of the trucks and each of the delivery stations includes:
acquiring a first position of each carrier and a second position of each delivery station;
for each of the trucks, determining from the first and second positions whether the truck is in the same sub-area as the respective outbound site;
and determining the distance between the truck and each delivery station according to the first position and the second position.
3. The outbound site determining 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, and the determining the cost between the nodes according to the position relationship with the truck and the outbound site as nodes comprises:
taking the transport vehicle as the first node, and taking the delivery station as a second station;
establishing a directed edge between the source node 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, 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 outbound site determination 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, the first formula comprising:
C(i,j)＝α·A+β·S，
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 when the ith first node and the jth second node are in the same sub-region, a is 0; when the ith first node and the jth second node are not in the same sub-region, A is 1; s is the distance between the ith first node and the jth second node.
5. The outbound site determining method according to claim 3 or 4, wherein the upper flow limit of the directed edge between the source point and each of the first nodes is 1, and the cost is 0; the upper flow limit between each first node and each second node is 1; for any second node, the upper flow limit 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 flow limit is a preset threshold, and the cost is 0.
6. The outbound site determining method according to claim 5, after solving the least-cost-max-flow problem according to the network flow model, further comprising:
and determining the station busyness upper limit of each directed edge of the second node and the sink by adopting a bisection method, so that when the flow of the directed edges of the second node and the sink is equal to the station busyness upper limit, the maximum flow of the network flow model is equal to the number of the carriers, and the total cost of the network flow model is minimum.
7. The delivery station determining method according to claim 5 or 6, wherein the transportation vehicle moves in one direction in the work area, the delivery station is paired with a warehousing station two by two, and for any of the delivery stations, the warehousing station corresponding to the delivery station is the warehousing station located in the moving direction of the transportation vehicle and closest to the delivery station;
the lower flow limit of the directed edge between the second node and the sink is the ratio of the amount of the goods to be warehoused at the corresponding warehousing site to the maximum cargo carrying capacity of each carrier.
8. An ex-warehouse site determination apparatus, comprising:
an acquisition module to acquire a set of vehicles in a work area and a set of ex-warehouse sites, the set of vehicles including one or more vehicles, the set of ex-warehouse sites including one or more ex-warehouse sites;
the model building module is used for determining the position relationship between each transport vehicle and each ex-warehouse site, determining the cost between the nodes according to the position relationship by taking the transport vehicles and the ex-warehouse sites as the nodes, and building a network flow model;
and the processing module is used for solving the problem of minimum cost and maximum flow according to the network flow model and determining the ex-warehouse station of each carrier.
9. An electronic device comprising a memory and a processor;
the memory for storing a computer program;
the processor, when executing the computer program, is configured to implement the outbound site determination method of any of claims 1 to 7.
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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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114186727A (en) * | 2021-12-02 | 2022-03-15 | 交通运输部水运科学研究所 | Multi-cycle logistics network planning method and system |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108804664A (en) * | 2018-06-08 | 2018-11-13 | 北京搜狗科技发展有限公司 | A kind of problem distribution method and relevant apparatus |
| KR20200015642A (en) * | 2020-01-25 | 2020-02-12 | 이승철 | Project/Task Intelligent Goal Management Method and Platform based on Super Tree |
| CN110880087A (en) * | 2019-10-21 | 2020-03-13 | 北京旷视机器人技术有限公司 | Method, device, warehousing system, equipment and medium for determining shelf position |
| CN110889599A (en) * | 2019-11-12 | 2020-03-17 | 北京旷视机器人技术有限公司 | Order processing method and device, warehousing system, computer equipment and storage medium |
| CN111780775A (en) * | 2020-06-17 | 2020-10-16 | 深圳优地科技有限公司 | Path planning method and device, robot and storage medium |
| CN111832802A (en) * | 2020-04-15 | 2020-10-27 | 北京旷视机器人技术有限公司 | Method, apparatus, system, device and medium for controlling goods-carrying vehicle |
| CN112184053A (en) * | 2020-10-14 | 2021-01-05 | 浙江华睿科技有限公司 | Task scheduling method, device and equipment |
| CN112308480A (en) * | 2020-09-07 | 2021-02-02 | 北京沃东天骏信息技术有限公司 | Goods scheduling method and device, electronic equipment and storage medium |
| CN112396362A (en) * | 2019-08-12 | 2021-02-23 | 北京京东乾石科技有限公司 | Method and device for determining driving destination and storage medium |
| CN112395376A (en) * | 2019-08-15 | 2021-02-23 | 纳恩博（北京）科技有限公司 | Map construction method and device, storage medium and electronic device |
-
2021
- 2021-06-02 CN CN202110615449.9A patent/CN113450049B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108804664A (en) * | 2018-06-08 | 2018-11-13 | 北京搜狗科技发展有限公司 | A kind of problem distribution method and relevant apparatus |
| CN112396362A (en) * | 2019-08-12 | 2021-02-23 | 北京京东乾石科技有限公司 | Method and device for determining driving destination and storage medium |
| CN112395376A (en) * | 2019-08-15 | 2021-02-23 | 纳恩博（北京）科技有限公司 | Map construction method and device, storage medium and electronic device |
| CN110880087A (en) * | 2019-10-21 | 2020-03-13 | 北京旷视机器人技术有限公司 | Method, device, warehousing system, equipment and medium for determining shelf position |
| CN110889599A (en) * | 2019-11-12 | 2020-03-17 | 北京旷视机器人技术有限公司 | Order processing method and device, warehousing system, computer equipment and storage medium |
| KR20200015642A (en) * | 2020-01-25 | 2020-02-12 | 이승철 | Project/Task Intelligent Goal Management Method and Platform based on Super Tree |
| CN111832802A (en) * | 2020-04-15 | 2020-10-27 | 北京旷视机器人技术有限公司 | Method, apparatus, system, device and medium for controlling goods-carrying vehicle |
| CN111780775A (en) * | 2020-06-17 | 2020-10-16 | 深圳优地科技有限公司 | Path planning method and device, robot and storage medium |
| CN112308480A (en) * | 2020-09-07 | 2021-02-02 | 北京沃东天骏信息技术有限公司 | Goods scheduling method and device, electronic equipment and storage medium |
| CN112184053A (en) * | 2020-10-14 | 2021-01-05 | 浙江华睿科技有限公司 | Task scheduling method, device and equipment |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114186727A (en) * | 2021-12-02 | 2022-03-15 | 交通运输部水运科学研究所 | Multi-cycle logistics network planning method and system |
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