CN113361739A - Method and device for generating goods picking path - Google Patents
Method and device for generating goods picking path Download PDFInfo
- Publication number
- CN113361739A CN113361739A CN202010151804.7A CN202010151804A CN113361739A CN 113361739 A CN113361739 A CN 113361739A CN 202010151804 A CN202010151804 A CN 202010151804A CN 113361739 A CN113361739 A CN 113361739A
- Authority
- CN
- China
- Prior art keywords
- picking
- path
- warehouse
- order
- picked
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 41
- 238000004088 simulation Methods 0.000 claims abstract description 79
- 238000003860 storage Methods 0.000 claims abstract description 66
- 238000011156 evaluation Methods 0.000 claims abstract description 57
- 239000011159 matrix material Substances 0.000 claims abstract description 22
- 238000004891 communication Methods 0.000 claims description 17
- 238000013329 compounding Methods 0.000 claims description 12
- 150000001875 compounds Chemical class 0.000 claims description 10
- 238000004590 computer program Methods 0.000 claims description 9
- 230000002068 genetic effect Effects 0.000 claims description 6
- 238000002922 simulated annealing Methods 0.000 claims description 6
- 238000010276 construction Methods 0.000 claims description 4
- 238000010845 search algorithm Methods 0.000 claims description 3
- 239000000126 substance Substances 0.000 claims description 3
- 238000012795 verification Methods 0.000 abstract description 8
- 238000010586 diagram Methods 0.000 description 13
- 230000006870 function Effects 0.000 description 7
- 238000009826 distribution Methods 0.000 description 6
- 230000008569 process Effects 0.000 description 6
- 230000008859 change Effects 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 4
- 230000003287 optical effect Effects 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 230000000644 propagated effect Effects 0.000 description 2
- 239000004065 semiconductor Substances 0.000 description 2
- 240000007594 Oryza sativa Species 0.000 description 1
- 235000007164 Oryza sativa Nutrition 0.000 description 1
- 239000002131 composite material Substances 0.000 description 1
- 230000001186 cumulative effect Effects 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 239000013307 optical fiber Substances 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000012887 quadratic function Methods 0.000 description 1
- 235000009566 rice Nutrition 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/087—Inventory or stock management, e.g. order filling, procurement or balancing against orders
- G06Q10/0875—Itemisation or classification of parts, supplies or services, e.g. bill of materials
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
Abstract
The invention discloses a method and a device for generating a goods picking path, and relates to the technical field of computers. One embodiment of the method comprises: acquiring a picking task, wherein the picking task indicates one or more storage positions to be picked in a warehouse and the weight of goods to be picked corresponding to the storage positions to be picked; generating a picking path corresponding to the picking task based on a path generation algorithm according to a distance matrix corresponding to the one or more storage positions to be picked, wherein the distance matrix indicates the distance between any two storage positions to be picked; evaluating the picking path by using a warehouse simulation system corresponding to the warehouse; and adjusting the path generation algorithm according to the evaluation result so as to regenerate the picking path according to the adjusted path generation algorithm. This embodiment has reduced the verification cost of choosing goods route, has improved the efficiency of choosing goods.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for generating a goods picking path.
Background
With the development of warehouse logistics, in order to improve the efficiency of warehouse logistics and save the cost, it is important to make a reasonable picking path to reduce the picking time of a picker in the warehouse.
At present, there are two main methods for generating the picking path in the warehouse: generating a picking path based on rules, namely setting picking orders for different roadways and different storage positions to be picked according to the plane layout of a warehouse and the distribution of commodities in the warehouse, and then generating a corresponding picking path based on the picking order corresponding to the storage positions to be picked in the given picking object; and generating a corresponding picking path according to the storage position to be picked in the given picking task based on a meta-heuristic path generation algorithm.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art: the picking path generated based on the rule is single and is only suitable for warehouses with roadways with single outlets; the picking path generated based on the meta-heuristic path generation algorithm only considers information such as warehouse layout and the like, and does not consider information such as picking speed change and the like in the picking process; in addition, the picking paths generated based on the prior art can be verified only by executing picking tasks in the warehouse, and the verification cost is high.
Disclosure of Invention
In view of this, embodiments of the present invention provide a method and an apparatus for generating a picking path, which can evaluate the picking path generated by a path generation algorithm based on a warehouse simulation system, and further adjust the path generation algorithm based on the evaluation result to regenerate the picking path, so as to reduce the time consumed for executing a picking task.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a method of generating a pick path, including:
acquiring a picking task, wherein the picking task indicates one or more storage positions to be picked in a warehouse and the weight of goods to be picked corresponding to the storage positions to be picked;
generating a picking path corresponding to the picking task based on a path generation algorithm according to a distance matrix corresponding to the one or more storage positions to be picked, wherein the distance matrix indicates the distance between any two storage positions to be picked;
evaluating the picking path by using a warehouse simulation system corresponding to the warehouse;
and adjusting the path generation algorithm according to the evaluation result so as to regenerate the picking path according to the adjusted path generation algorithm.
Optionally, the method further comprises: judging whether the difference of the evaluation results corresponding to the picking paths generated before and after the adjustment of the path generation algorithm is within the threshold difference, and continuously adjusting the path generation algorithm to regenerate the picking paths under the condition that the difference of the evaluation results is not within the threshold difference.
Optionally, the warehouse simulation system is built based on the following steps:
establishing road network information in the warehouse simulation system, wherein the road network information indicates one or more roadways in the warehouse and the communication relation among the roadways;
adding a shelf in the warehouse simulation system, wherein the shelf indicates position information and size information corresponding to one or more storage positions to be picked in the warehouse;
associating the shelf with the road network information;
adding one or more compounding stations in the warehouse simulation system, the compounding stations being used to verify the picking tasks and indicating the start and end points of the picking paths;
one or more pickers are added in the warehouse simulation system, and the starting point and the end point corresponding to the pickers are set as the compound station.
Alternatively,
the evaluating the picking path by using a warehouse simulation system corresponding to the warehouse comprises the following steps:
randomly assigning the picking tasks to one or more of the pickers in the warehouse simulation system;
while the order picker performs the order picking task along the generated order picking path, the speed of the order picker is continuously changed according to the weight corresponding to the picked items;
calculating one or more of the following evaluation results corresponding to the order picker performing the order picking task according to the order picking path according to the speed of the order picker: the total time consumption corresponding to the order picking task, the average time consumption corresponding to one or more goods in the order picking task, the walking time consumption of the order picker, the ratio of the walking time consumption of the order picker to the total time consumption of the order picking task, and the time consumption of the order picker passing through a tunnel in the order picking path.
Optionally, the path generation algorithm is any one of: ant colony algorithm, tabu search, simulated annealing, genetic algorithm.
To achieve the above object, according to another aspect of an embodiment of the present invention, there is provided an apparatus for generating a pick path, including: the system comprises a picking task acquisition module, a picking path generation module and a picking path evaluation module; wherein the content of the first and second substances,
the picking task acquisition module is used for acquiring picking tasks, and the picking tasks indicate one or more storage positions to be picked in a warehouse and the weight of goods to be picked corresponding to the storage positions to be picked;
the picking path generating module is used for generating a picking path corresponding to the picking task based on a path generating algorithm according to a distance matrix corresponding to the one or more storage positions to be picked, and the distance matrix indicates the distance between any two storage positions to be picked;
the picking path evaluation module is used for evaluating the picking path by using a warehouse simulation system corresponding to the warehouse;
the picking path generation module is also used for adjusting the path generation algorithm according to the evaluation result so as to regenerate the picking path according to the adjusted path generation algorithm.
Optionally, the picking path generating module is further configured to,
judging whether the difference of the evaluation results corresponding to the picking paths generated before and after the adjustment of the path generation algorithm is within the threshold difference, and continuously adjusting the path generation algorithm to regenerate the picking paths under the condition that the difference of the evaluation results is not within the threshold difference.
Optionally, the method further comprises: a warehouse simulation system construction module; the warehouse simulation system building module is used for building the warehouse simulation system based on the following steps:
establishing road network information in the warehouse simulation system, wherein the road network information indicates one or more roadways in the warehouse and the communication relation among the roadways;
adding a shelf in the warehouse simulation system, wherein the shelf indicates position information and size information corresponding to one or more storage positions to be picked in the warehouse;
associating the shelf with the road network information;
adding one or more compounding stations in the warehouse simulation system, the compounding stations being used to verify the picking tasks and indicating the start and end points of the picking paths;
one or more pickers are added in the warehouse simulation system, and the starting point and the end point corresponding to the pickers are set as the compound station.
Optionally, the evaluating the pick path using a warehouse simulation system corresponding to the warehouse comprises:
randomly assigning the picking tasks to one or more of the pickers in the warehouse simulation system;
while the order picker performs the order picking task along the generated order picking path, the speed of the order picker is continuously changed according to the weight corresponding to the picked items;
calculating one or more of the following evaluation results corresponding to the order picker performing the order picking task according to the order picking path according to the speed of the order picker: the total time consumption corresponding to the order picking task, the average time consumption corresponding to one or more goods in the order picking task, the walking time consumption of the order picker, the ratio of the walking time consumption of the order picker to the total time consumption of the order picking task, and the time consumption of the order picker passing through a tunnel in the order picking path.
Optionally, the path generation algorithm is any one of: ant colony algorithm, tabu search algorithm, simulated annealing algorithm, genetic algorithm.
To achieve the above object, according to another aspect of an embodiment of the present invention, there is provided an electronic device for generating a pick path, including: one or more processors; a storage device for storing one or more programs which, when executed by the one or more processors, cause the one or more processors to implement any of the methods of generating a pick path as described above.
To achieve the above object, according to another aspect of embodiments of the present invention, there is provided a computer readable medium having stored thereon a computer program, characterized in that the program, when executed by a processor, implements any of the methods of generating a pick path as described above.
One embodiment of the above invention has the following advantages or benefits: because the warehouse simulation system is adopted to evaluate the picking path and further adjust the path generation algorithm, the technical problem of high verification cost caused by the fact that the picking task needs to be executed in the warehouse to verify the picking path in the prior art is solved, the verification cost of the picking path is reduced, meanwhile, the picking path is regenerated through the adjusted path generation algorithm, the time required for executing the picking task according to the regenerated picking path is reduced, and the picking efficiency is improved; in addition, when the warehouse simulation system is used for evaluating the picking path, information such as random distribution of picking tasks, dynamic change of picking speed and the like is considered, so that the evaluation of the picking path is more reliable and effective.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
fig. 1 is a schematic diagram of a main flow of a method of generating a pick path according to an embodiment of the invention;
FIG. 2 is a schematic diagram of the main flow of another method of generating a pick path according to an embodiment of the present invention;
fig. 3 is a schematic diagram of the main flow of a pick-up path evaluation method according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a main flow of a warehouse simulation system building method according to an embodiment of the invention;
fig. 5 is a schematic diagram of the main modules of an apparatus for generating a pick path according to an embodiment of the present invention;
FIG. 6 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 7 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a schematic diagram of a main flow of a method of generating a pick path according to an embodiment of the invention; as shown in fig. 1, the method for generating a pick-up path may specifically include the following steps:
step S101, a picking task is obtained, and the picking task indicates one or more storage positions to be picked in a warehouse and the weight of goods to be picked corresponding to the storage positions to be picked. In particular, with reference to table 1 below, one pick order indicates a pick level comprising: cell1, Cell2, Cell3 and Cell4, and the weight of the corresponding cargo to be picked is 8 kg, 2 kg, 7 kg and 4 kg respectively.
Table 1 pick task example
| Storage position to be picked | Weight of goods to be picked (kilogram) |
| Cell1 | 8 |
| Cell2 | 2 |
| Cell3 | 7 |
| Cell4 | 4 |
And step S102, generating a picking path corresponding to the picking task based on a path generation algorithm according to the distance matrix corresponding to the one or more storage positions to be picked, wherein the distance matrix indicates the distance between any two storage positions to be picked. In this embodiment, the distance matrix indicates the shortest distance between any two storage locations to be sorted, that is, the length corresponding to the shortest path, and may be calculated by using dijstra algorithm according to the warehouse layout and the distribution of the storage locations to be sorted in the warehouse. In particular, with reference to table 2, the distance matrix calculated from the storage positions to be sorted shown in table 1 above is as follows:
TABLE 2 distance matrix schematic
| Storage position/distance (rice) to be picked | Cell1 | Cell2 | Cell3 | Cell4 |
| Cell1 | 0 | 52 | 18 | 48 |
| Cell2 | 52 | 0 | 93 | 41 |
| Cell3 | 18 | 93 | 0 | 30 |
| Cell4 | 48 | 41 | 30 | 0 |
On the basis, based on the distance matrix, the picking path obtained by adopting the path generation algorithm is Cell1 → Cell3 → Cell4 → Cell2 → Cell1, namely, goods are picked in the order of the position to be picked Cell1, the position to be picked Cell3, the position to be picked Cell4, the position to be picked Cell2 and the position to be picked Cell1 to execute a picking task, and the total length of the picking path is the sum 141 of the distances between the positions to be picked passing by the order (namely, the sum of 18, 30, 41 and 52). The path generation algorithm used in the present embodiment is any one of an ant colony algorithm, tabu search, simulated annealing, and genetic algorithm, and it is understood that other meta-heuristic algorithms may be used to generate the picking path.
And step S103, evaluating the picking path by using a warehouse simulation system corresponding to the warehouse.
Specifically, the evaluating the picking path by using a warehouse simulation system corresponding to the warehouse comprises: randomly assigning the picking tasks to one or more of the pickers in the warehouse simulation system; while the order picker performs the order picking task along the generated order picking path, the speed of the order picker is continuously changed according to the weight corresponding to the picked items; calculating one or more of the following evaluation results corresponding to the order picker performing the order picking task according to the order picking path according to the speed of the order picker: the total time consumption corresponding to the order picking task, the average time consumption corresponding to one or more goods in the order picking task, the walking time consumption of the order picker, the ratio of the walking time consumption of the order picker to the total time consumption of the order picking task, and the time consumption of the order picker passing through a tunnel in the order picking path.
It will be appreciated that in an actual warehouse operation there may be one or more pickers, one or more pickers performing the picking tasks, and one or more pickers being performed. Therefore, when the warehouse simulation system is used for simulating and executing the picking task, in order to more effectively verify the quality of the picking path in practical application, the picking task is randomly distributed to the pickers, so that the randomness of time for distributing the picking task, the randomness of the pickers for receiving the picking task and the like are ensured. In addition, since the weight of the goods carried or picked increases when the picker picks the goods, the walking speed or picking speed of the picker itself is also affected. Thus, the speed of the picker is dynamically varied as the weight of the picked items changes during the picking task performed by the picker along the generated picking path. In this manner, the warehouse simulation system may be used to more truly and efficiently evaluate the pick path.
In an alternative embodiment, the warehouse simulation system is constructed based on the following steps: establishing road network information in the warehouse simulation system, wherein the road network information indicates one or more roadways in the warehouse and the communication relation among the roadways; adding a shelf in the warehouse simulation system, wherein the shelf indicates position information and size information corresponding to one or more storage positions to be picked in the warehouse; associating the shelf with the road network information; adding one or more compounding stations in the warehouse simulation system, the compounding stations being used to verify the picking tasks and indicating the start and end points of the picking paths; one or more pickers are added in the warehouse simulation system, and the starting point and the end point corresponding to the pickers are set as the compound station.
And step S104, adjusting the path generation algorithm according to the evaluation result so as to regenerate the picking path according to the adjusted path generation algorithm. Specifically, the evaluation result is taken as the total time consumption corresponding to the picking task for example, and after the total time consumption corresponding to the picking task is obtained, the neighborhood search method can be adopted to adjust and optimize the path generation algorithm, so that the total time consumption required when the picking task is executed according to the picking path regenerated by the adjusted path generation algorithm is less.
In an alternative embodiment, the in-bin layout of the warehouse is adjusted according to the evaluation result. It can be understood that the total time consumption required for executing the picking task is related to the picking path and depends on the layout in the warehouse, such as the number of the roadways in the warehouse, whether the roadways in the warehouse are communicated or not, the width of the roadways in the warehouse, the distribution of the storage positions to be picked in the warehouse, and the like, so that after the evaluation result corresponding to one or more picking paths is obtained, the layout in the warehouse can be adjusted according to the evaluation result, so that the layout in the warehouse is more favorable for fast picking. Specifically, taking the ratio of the time consumed by the order picker to the total time consumed in the order picking heat in the evaluation result as an example, if the ratios corresponding to different order picking paths or order picking tasks are all higher (for example, higher than 70%), it indicates that the distance the order picker needs to walk during order picking is longer or the walking speed is lower: for the case of longer distance, the more dense arrangement of the storage positions to be picked can be considered, so that the distance between the storage positions to be picked is shortened, and the total distance required by a picker to walk is shortened; under the condition that the walking speed of the order picker is low, the roadway congestion may be caused by the fact that a plurality of order pickers simultaneously execute order picking tasks in the warehouse, and then the walking speed of the order picker is low, so that the roadway frequently passed by the order picker or the roadway with serious congestion can be considered to be widened.
In an optional embodiment, the method further comprises: judging whether the difference of the evaluation results corresponding to the picking paths generated before and after the adjustment of the path generation algorithm is within the threshold difference, and continuously adjusting the path generation algorithm to regenerate the picking paths under the condition that the difference of the evaluation results is not within the threshold difference. That is, by determining the optimization effect of the path generation algorithm, it is determined whether the path generation algorithm needs to be further optimized. Specifically, under the condition that the difference of the evaluation results is within the threshold value difference, the picking path generated after the adjustment of the current path generation algorithm is used as the optimal picking path corresponding to the picking task; and under the condition that the difference of the evaluation results is not within the threshold value difference, continuously using the evaluation result corresponding to the picking path generated after the adjustment of the current path generation algorithm to adjust the path generation algorithm so as to regenerate the picking path. Therefore, the path generation algorithm is continuously optimized through continuous iteration, and the corresponding regenerated picking path is also not short.
Specifically, the evaluation result is taken as the total time consumption of the picking task, and the threshold difference is 10 for example, if the difference between the total time consumption corresponding to the picking task executed according to the initially generated picking path and the total time consumption corresponding to the picking task executed according to the newly generated picking path is greater than 10, the path generation algorithm continues to be repeatedly optimized; and if the difference between the total time consumption corresponding to the order picking task executed according to the initially generated order picking path and the total time consumption corresponding to the order picking task executed according to the newly generated order picking path is larger than 10, the path generation algorithm is not continuously and repeatedly optimized, and the current newly generated order picking path is used as the final order picking path corresponding to the order picking task.
In addition, besides whether the evaluation result difference is within the threshold value range or not, whether the path generation algorithm is continuously adjusted or not can be judged according to the total times of adjusting the path generation algorithm or the total time consumed by adjusting the path generation algorithm in order to reasonably control the resources and time consumed by adjusting the path generation algorithm to improve the production efficiency of the picking path. Specifically, a threshold number of times (e.g., 50 times) and a threshold time (e.g., 12h) are preset, and if the adjustment number of the path generation algorithm reaches the threshold number of times, the path production algorithm is not adjusted any more, or if the total time of cumulative consumption of the adjustment of the path generation algorithm reaches the threshold time, the path production algorithm is not adjusted any more.
Based on the embodiment, the warehouse simulation system is adopted to evaluate the picking path, and then the technical means of adjusting the path generation algorithm is adopted, so that the technical problem of high verification cost caused by the fact that the picking task needs to be executed in the warehouse to verify the picking path in the prior art is solved, the verification cost of the picking path is reduced, meanwhile, the picking path is regenerated through the adjusted path generation algorithm, the time required for executing the picking task according to the regenerated picking path is reduced, and the picking efficiency is improved; in addition, when the warehouse simulation system is used for evaluating the picking path, information such as random distribution of picking tasks, dynamic change of picking speed and the like is considered, so that the evaluation of the picking path is more reliable and effective.
Referring to fig. 2, on the basis of the above embodiment, an embodiment of the present invention provides a method for generating a pick-up path, which may specifically include the following steps:
step S201, a picking task is obtained, where the picking task indicates one or more storage locations to be picked in the warehouse and the weight of the goods to be picked corresponding to the storage locations to be picked.
Step S202, according to the distance matrix corresponding to the one or more storage positions to be picked, based on a path generation algorithm, a picking path corresponding to the picking task is generated, and the distance matrix indicates the distance between any two storage positions to be picked.
Step S203, using the warehouse simulation system corresponding to the warehouse to evaluate the picking path.
And S204, adjusting the path generation algorithm according to the evaluation result so as to regenerate the picking path according to the adjusted path generation algorithm.
Step S205, determining whether the difference of the evaluation results corresponding to the picking path generated before the adjustment of the path generation algorithm and the picking path generated after the adjustment is within the threshold difference. If the evaluation result is within the threshold difference, the process of generating the picking path is ended, and the picking path regenerated in the step S204 is taken as the optimal picking path corresponding to the picking task; if the evaluation result is not within the threshold difference, the step S202 and the subsequent steps are repeated. The continuous iteration enables the path generation algorithm to be continuously optimized, and the regenerated picking path is not short and optimal.
Specifically, the evaluation result is taken as the total time consumption of the picking task, and the threshold difference is 10 for example, if the difference between the total time consumption corresponding to the picking task executed according to the initially generated picking path and the total time consumption corresponding to the picking task executed according to the newly generated picking path is greater than 10, the path generation algorithm continues to be repeatedly optimized; and if the difference between the total time consumption corresponding to the order picking task executed according to the initially generated order picking path and the total time consumption corresponding to the order picking task executed according to the newly generated order picking path is larger than 10, the path generation algorithm is not continuously and repeatedly optimized, and the current newly generated order picking path is used as the final order picking path corresponding to the order picking task.
Referring to fig. 3, on the basis of the above embodiment, in order to more clearly and specifically describe the evaluation of the picking path by using the warehouse simulation system, the embodiment of the present invention provides a picking path evaluation method to further explain step S103 in the above embodiment, which specifically includes the following steps:
step S1031, randomly assigning the picking tasks to one or more of the pickers in the warehouse simulation system. It will be appreciated that in an actual warehouse operation there may be one or more pickers, one or more pickers performing the picking tasks, and one or more pickers being performed. Therefore, when the warehouse simulation system is used for simulating and executing the picking task, in order to more effectively verify the quality of the picking path in practical application, the picking task is randomly distributed to the pickers, so that the randomness of time for distributing the picking task, the randomness of the pickers for receiving the picking task and the like are ensured.
In step S1032, the speed of the order picker is continuously changed according to the corresponding weight of the picked item when the order picker performs the order picking task along the generated order picking path. The speed of the picker's own walking or picking speed is also affected as the weight of the carried or picked goods increases when the picker picks the goods. Thus, the speed of the picker is dynamically varied as the weight of the picked items changes during the picking task performed by the picker along the generated picking path. Specifically, the simple linear relationship between the speed of the picker and the weight of the picked goods is taken as an example for explanation, and it is assumed that the relationship between the walking speed of the picker and the weight of the picked goods satisfies the following linear formula:
v＝1.5-0.01*weight
wherein v is the walking speed of the order picker, the unit is m/s, weight is the weight of the order picked by the order picker, the unit is kilogram, 1.5 and 0.01 are two parameters, and can be adjusted according to the actual situation, and then according to the linear relation, the larger the weight of the order picked by the order picker is, the smaller the walking speed of the order picker is. Besides, the relationship between the weight of the picked goods and the walking speed of the picker can be expressed by a quadratic function, an exponential function or a simple mapping relation.
Step S1033, calculating one or more evaluation results corresponding to the order picker performing the order picking task according to the order picking path according to the speed of the order picker. The evaluation result in this embodiment includes one or more of the following: the total time consumption corresponding to the order picking task, the average time consumption corresponding to one or more goods in the order picking task, the walking time consumption of the order picker, the ratio of the walking time consumption of the order picker to the total time consumption of the order picking task, and the time consumption of the order picker passing through a tunnel in the order picking path.
On the basis, referring to table 1 and table 2, taking the evaluation result as the total time consumption corresponding to the picking task and the relationship between the walking speed of the picker and the weight of the picked goods satisfying the above linear formula as an example, the total time consumption corresponding to the picking task executed according to the picking path Cell1 → Cell3 → Cell4 → Cell2 → Cell1 in the warehouse simulation system can be calculated according to the following method:
when the pickers pass through Cell1 → Cell3, the walking distance of the pickers is 18, the walking speed of the pickers is 1.5-0.01 × 8-1.42, and the walking time is 18/1.42-12.68;
when the pickers pass through Cell3 → Cell4, the walking distance of the pickers is 30, the walking speed of the pickers is 1.5-0.01 ═ 1.35, and the walking time is 30/1.35 ═ 22.22;
when the person passes through Cell4 → Cell2, the distance traveled by the picker is 41, the walking degree of the picker is 1.5-0.01 (8+7+4) ═ 1.31, and the walking time is 41/1.31 ═ 31.30;
when the picker travels through Cell2 → Cell1, the walking distance of the picker is 52, the walking speed of the picker is 1.5-0.01 (8+7+4+2) ═ 1.29, and the walking time is 52/1.29 ═ 40.31;
in summary, the total time consumption for the picking task calculated in the warehouse simulation system in consideration of the dynamic variation of the picker speed is 12.68+22.22+31.30+40.31 (in seconds) 106.51, whereas the total time consumption for the picking task calculated directly without consideration of the dynamic variation is 141/1.5 (in seconds) 94. Therefore, when the picking task is simulated and executed in the simulation model according to the picking path, the picking path can be more effectively and truly evaluated by adding factors such as dynamic change of the walking speed of a picker and the like.
Referring to fig. 4, on the basis of the above embodiment, the embodiment of the present invention provides a warehouse simulation system construction method, which may specifically include the following steps:
step S401, establishing road network information in the warehouse simulation system, wherein the road network information indicates one or more lanes in the warehouse and the communication relationship among the lanes. More specifically, the key nodes of the road network information indicate exits or entrances at two ends of a roadway, positions of a composite station and the like, each key node can be represented by a NetworkNode object, one or more names of other key nodes, corresponding communication relations, distance information and the like are stored in each key node, and the key nodes with the communication relations are connected with each other by straight lines.
Step S402, adding a shelf in the warehouse simulation system, wherein the shelf indicates position information and size information corresponding to one or more storage positions to be picked in the warehouse. Specifically, the position information and the size information of the shelves corresponding to one or more bins to be picked can be associated by using a global table accessible from any position in the warehouse simulation system.
Step S403, associating the shelf with the road network information. The information of the goods shelf and the road network can truly reflect the relative positions and communication relations of the goods shelf, the laneways, the compound platforms and the like in the real warehouse.
Step S404, adding one or more compound stations in the warehouse simulation system, wherein the compound stations are used for verifying the picking task and indicate the starting point and the end point of the picking path.
Step S405, adding one or more pickers in the warehouse simulation system, and setting a start point and an end point corresponding to the pickers as the compound station.
Referring to fig. 5, on the basis of the above embodiment, an embodiment of the present invention provides an apparatus 500 for generating a pick path, including: a picking task obtaining module 501, a picking path generating module 502 and a picking path evaluating module 503; wherein the content of the first and second substances,
the picking task obtaining module 501 is configured to obtain a picking task, where the picking task indicates one or more storage locations to be picked in a warehouse and a weight of goods to be picked corresponding to the storage locations to be picked;
the picking path generating module 502 is configured to generate a picking path corresponding to the picking task for the first time based on a path generating algorithm according to a distance matrix corresponding to the one or more storage locations to be picked, where the distance matrix indicates a distance between any two of the storage locations to be picked;
the picking path evaluation module 503 is configured to evaluate the picking path by using a warehouse simulation system corresponding to the warehouse;
the picking path generating module 502 is further configured to adjust the path generating algorithm according to the evaluation result, so as to regenerate the picking path according to the adjusted path generating algorithm.
In an alternative embodiment, the pick-up path generation module is further configured to,
judging whether the difference of the evaluation results corresponding to the picking paths generated before and after the adjustment of the path generation algorithm is within the threshold difference, and continuously adjusting the path generation algorithm to regenerate the picking paths under the condition that the difference of the evaluation results is not within the threshold difference.
In addition, in addition to using whether the evaluation result difference is within the threshold value range to judge whether to continue to adjust the path generation algorithm, whether to continue to adjust the path generation algorithm can be judged according to the total times of adjusting the path generation algorithm or the total time consumed by adjusting the path generation algorithm in order to reasonably control the resources and time consumed by adjusting the path generation algorithm to improve the production efficiency of the picking path.
In an optional embodiment, the method further comprises: a warehouse simulation system build module 504; wherein the warehouse simulation system building module 504 is configured to build the warehouse simulation system based on the following steps:
establishing road network information in the warehouse simulation system, wherein the road network information indicates one or more roadways in the warehouse and the communication relation among the roadways;
adding a shelf in the warehouse simulation system, wherein the shelf indicates position information and size information corresponding to one or more storage positions to be picked in the warehouse;
associating the shelf with the road network information;
adding one or more compounding stations in the warehouse simulation system, the compounding stations being used to verify the picking tasks and indicating the start and end points of the picking paths;
one or more pickers are added in the warehouse simulation system, and the starting point and the end point corresponding to the pickers are set as the compound station.
In an alternative embodiment, the evaluating the pick path using a warehouse simulation system corresponding to the warehouse comprises:
randomly assigning the picking tasks to one or more of the pickers in the warehouse simulation system;
while the order picker performs the order picking task along the generated order picking path, the speed of the order picker is continuously changed according to the weight corresponding to the picked items;
calculating one or more of the following evaluation results corresponding to the order picker performing the order picking task according to the order picking path according to the speed of the order picker: the total time consumption corresponding to the order picking task, the average time consumption corresponding to one or more goods in the order picking task, the walking time consumption of the order picker, the ratio of the walking time consumption of the order picker to the total time consumption of the order picking task, and the time consumption of the order picker passing through a tunnel in the order picking path.
In an optional embodiment, the path generation algorithm is any one of the following: ant colony algorithm, tabu search algorithm, simulated annealing algorithm, genetic algorithm.
Fig. 6 illustrates an exemplary system architecture 600 of a method of generating a pick path or a method of generating a pick path device to which embodiments of the present invention may be applied.
As shown in fig. 6, the system architecture 600 may include terminal devices 601, 602, 603, a network 604, and a server 605. The network 604 serves to provide a medium for communication links between the terminal devices 601, 602, 603 and the server 605. Network 604 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.
A user may use the terminal devices 601, 602, 603 to interact with the server 605 via the network 604 to receive or send messages or the like. Various communication client applications, such as shopping applications, web browser applications, search applications, instant messaging tools, mailbox clients, social platform software, and the like, may be installed on the terminal devices 601, 602, and 603.
The terminal devices 601, 602, 603 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 605 may be a server that provides various services, such as a background management server that supports shopping websites browsed by users using the terminal devices 601, 602, and 603. The background management server can analyze and process the received data such as the product information inquiry request and feed back the processing result to the terminal equipment.
It should be noted that the method for generating the order picking path provided by the embodiment of the present invention is generally executed by the server 605, and accordingly, the method and apparatus for generating the order picking path are generally disposed in the server 605.
It should be understood that the number of terminal devices, networks, and servers in fig. 6 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 7, shown is a block diagram of a computer system 700 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 7, the computer system 700 includes a Central Processing Unit (CPU)701, which can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for the operation of the system 700 are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
The following components are connected to the I/O interface 705: an input portion 706 including a keyboard, a mouse, and the like; an output section 707 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 708 including a hard disk and the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read out therefrom is mounted into the storage section 708 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 709, and/or installed from the removable medium 711. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 701.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor comprises a picking task obtaining module and a picking path generating module. Where the names of these modules do not in some cases constitute a limitation of the module itself, for example, the pick order task picking module may also be described as a "module for picking a pick order task".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: acquiring a picking task, wherein the picking task indicates one or more storage positions to be picked in a warehouse and the weight of goods to be picked corresponding to the storage positions to be picked; the following steps are repeatedly executed until the repeated execution termination condition is met so as to generate a picking path: primarily generating a picking path corresponding to the picking task based on a path generation algorithm according to a distance matrix corresponding to the one or more storage positions to be picked, wherein the distance matrix indicates the distance between any two storage positions to be picked; evaluating the picking path by using a warehouse simulation system corresponding to the warehouse; and adjusting the path generation algorithm according to the evaluation result so as to regenerate the picking path according to the adjusted path generation algorithm.
According to the technical scheme of the embodiment of the invention, the warehouse simulation system is adopted to evaluate the picking path and further adjust the path generation algorithm, so that the technical problem of high verification cost caused by the fact that the picking task needs to be executed in the warehouse to verify the picking path in the prior art is solved, the verification cost of the picking path is reduced, meanwhile, the picking path is regenerated through the adjusted path generation algorithm, the time required for executing the picking task according to the regenerated picking path is reduced, and the picking efficiency is improved; in addition, when the warehouse simulation system is used for evaluating the picking path, information such as random distribution of picking tasks, dynamic change of picking speed and the like is considered, so that the evaluation of the picking path is more reliable and effective.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (12)
1. A method of generating a pick path, comprising:
acquiring a picking task, wherein the picking task indicates one or more storage positions to be picked in a warehouse and the weight of goods to be picked corresponding to the storage positions to be picked;
generating a picking path corresponding to the picking task based on a path generation algorithm according to a distance matrix corresponding to the one or more storage positions to be picked, wherein the distance matrix indicates the distance between any two storage positions to be picked;
evaluating the picking path by using a warehouse simulation system corresponding to the warehouse;
and adjusting the path generation algorithm according to the evaluation result so as to regenerate the picking path according to the adjusted path generation algorithm.
2. The method of generating a pick path as claimed in claim 1, further comprising:
judging whether the difference of the evaluation results corresponding to the picking paths generated before and after the adjustment of the path generation algorithm is within the threshold difference, and continuously adjusting the path generation algorithm to regenerate the picking paths under the condition that the difference of the evaluation results is not within the threshold difference.
3. The method of generating a pickpath as claimed in claim 1, wherein the warehouse simulation system is constructed based on the steps of:
establishing road network information in the warehouse simulation system, wherein the road network information indicates one or more roadways in the warehouse and the communication relation among the roadways;
adding a shelf in the warehouse simulation system, wherein the shelf indicates position information and size information corresponding to one or more storage positions to be picked in the warehouse;
associating the shelf with the road network information;
adding one or more compounding stations in the warehouse simulation system, the compounding stations being used to verify the picking tasks and indicating the start and end points of the picking paths;
one or more pickers are added in the warehouse simulation system, and the starting point and the end point corresponding to the pickers are set as the compound station.
4. The method of generating a pick path as claimed in claim 3, wherein said evaluating the pick path using a warehouse simulation system corresponding to the warehouse comprises:
randomly assigning the picking tasks to one or more of the pickers in the warehouse simulation system;
while the order picker performs the order picking task along the generated order picking path, the speed of the order picker is continuously changed according to the weight corresponding to the picked items;
calculating one or more of the following evaluation results corresponding to the order picker performing the order picking task according to the order picking path according to the speed of the order picker: the total time consumption corresponding to the order picking task, the average time consumption corresponding to one or more goods in the order picking task, the walking time consumption of the order picker, the ratio of the walking time consumption of the order picker to the total time consumption of the order picking task, and the time consumption of the order picker passing through a tunnel in the order picking path.
5. The method of generating a pick path of claim 1,
the path generation algorithm is any one of the following: ant colony algorithm, tabu search, simulated annealing, genetic algorithm.
6. An apparatus for generating a pick path, comprising: the system comprises a picking task acquisition module, a picking path generation module and a picking path evaluation module; wherein the content of the first and second substances,
the picking task acquisition module is used for acquiring picking tasks, and the picking tasks indicate one or more storage positions to be picked in a warehouse and the weight of goods to be picked corresponding to the storage positions to be picked;
the picking path generating module is used for generating a picking path corresponding to the picking task based on a path generating algorithm according to a distance matrix corresponding to the one or more storage positions to be picked, and the distance matrix indicates the distance between any two storage positions to be picked;
the picking path evaluation module is used for evaluating the picking path by using a warehouse simulation system corresponding to the warehouse;
the picking path generation module is also used for adjusting the path generation algorithm according to the evaluation result so as to regenerate the picking path according to the adjusted path generation algorithm.
7. The apparatus for generating a pick path as claimed in claim 6, wherein the pick path generation module is further configured to,
judging whether the difference of the evaluation results corresponding to the picking paths generated before and after the adjustment of the path generation algorithm is within the threshold difference, and continuously adjusting the path generation algorithm to regenerate the picking paths under the condition that the difference of the evaluation results is not within the threshold difference.
8. The apparatus for generating a pick path of claim 6, further comprising: a warehouse simulation system construction module; the warehouse simulation system building module is used for building the warehouse simulation system based on the following steps:
establishing road network information in the warehouse simulation system, wherein the road network information indicates one or more roadways in the warehouse and the communication relation among the roadways;
adding a shelf in the warehouse simulation system, wherein the shelf indicates position information and size information corresponding to one or more storage positions to be picked in the warehouse;
associating the shelf with the road network information;
adding one or more compounding stations in the warehouse simulation system, the compounding stations being used to verify the picking tasks and indicating the start and end points of the picking paths;
one or more pickers are added in the warehouse simulation system, and the starting point and the end point corresponding to the pickers are set as the compound station.
9. The apparatus for generating a pick path as claimed in claim 8, wherein said evaluating the pick path using a warehouse simulation system corresponding to the warehouse comprises:
randomly assigning the picking tasks to one or more of the pickers in the warehouse simulation system;
while the order picker performs the order picking task along the generated order picking path, the speed of the order picker is continuously changed according to the weight corresponding to the picked items;
calculating one or more of the following evaluation results corresponding to the order picker performing the order picking task according to the order picking path according to the speed of the order picker: the total time consumption corresponding to the order picking task, the average time consumption corresponding to one or more goods in the order picking task, the walking time consumption of the order picker, the ratio of the walking time consumption of the order picker to the total time consumption of the order picking task, and the time consumption of the order picker passing through a tunnel in the order picking path.
10. The apparatus for generating a pick path of claim 6,
the path generation algorithm is any one of the following: ant colony algorithm, tabu search algorithm, simulated annealing algorithm, genetic algorithm.
11. An electronic device for generating a pick path, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-5.
12. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010151804.7A CN113361739B (en) | 2020-03-06 | 2020-03-06 | Method and device for generating picking path |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010151804.7A CN113361739B (en) | 2020-03-06 | 2020-03-06 | Method and device for generating picking path |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113361739A true CN113361739A (en) | 2021-09-07 |
| CN113361739B CN113361739B (en) | 2024-04-12 |
Family
ID=77524157
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010151804.7A Active CN113361739B (en) | 2020-03-06 | 2020-03-06 | Method and device for generating picking path |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113361739B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117333059A (en) * | 2023-09-28 | 2024-01-02 | 北京工商大学 | Warehouse picking path time estimation method |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101739812A (en) * | 2009-12-10 | 2010-06-16 | 浙江师范大学 | Route optimizing method for logistic distribution vehicle |
| CN104992241A (en) * | 2015-07-02 | 2015-10-21 | 北京京东尚科信息技术有限公司 | Goods picking path generation method and generation apparatus, and corresponding storage management system |
| CN109919345A (en) * | 2017-12-12 | 2019-06-21 | 北京京东尚科信息技术有限公司 | Picking paths planning method and device |
| CN110388921A (en) * | 2018-04-17 | 2019-10-29 | 北京京东振世信息技术有限公司 | Picking air navigation aid and device |
| CN110531759A (en) * | 2019-08-02 | 2019-12-03 | 深圳大学 | Path generating method, device, computer equipment and storage medium are explored by robot |
| CN110599090A (en) * | 2019-09-04 | 2019-12-20 | 浙江明度智控科技有限公司 | Warehouse-out management method, server and storage medium |
| US20200023518A1 (en) * | 2018-07-17 | 2020-01-23 | Fanuc Corporation | Robot system |
-
2020
- 2020-03-06 CN CN202010151804.7A patent/CN113361739B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101739812A (en) * | 2009-12-10 | 2010-06-16 | 浙江师范大学 | Route optimizing method for logistic distribution vehicle |
| CN104992241A (en) * | 2015-07-02 | 2015-10-21 | 北京京东尚科信息技术有限公司 | Goods picking path generation method and generation apparatus, and corresponding storage management system |
| CN109919345A (en) * | 2017-12-12 | 2019-06-21 | 北京京东尚科信息技术有限公司 | Picking paths planning method and device |
| CN110388921A (en) * | 2018-04-17 | 2019-10-29 | 北京京东振世信息技术有限公司 | Picking air navigation aid and device |
| US20200023518A1 (en) * | 2018-07-17 | 2020-01-23 | Fanuc Corporation | Robot system |
| CN110531759A (en) * | 2019-08-02 | 2019-12-03 | 深圳大学 | Path generating method, device, computer equipment and storage medium are explored by robot |
| CN110599090A (en) * | 2019-09-04 | 2019-12-20 | 浙江明度智控科技有限公司 | Warehouse-out management method, server and storage medium |
Non-Patent Citations (3)
| Title |
|---|
| LI MA: "An Improved Jump Point Search Algorithm for Home Service Robot Path Planning", 《2019 CHINESE CONTROL AND DECISION CONFERENCE (CCDC)》, pages 2477 - 2482 * |
| 吴秀丽: "智慧仓内的智能算法应用现状综述", 《物流技术与应用》, pages 118 - 123 * |
| 孙军艳;牛亚儒;苏宝;张媛媛;: "双区型仓库动态拣货策略的设计及路径优化研究", 包装工程, no. 23, pages 11 - 18 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117333059A (en) * | 2023-09-28 | 2024-01-02 | 北京工商大学 | Warehouse picking path time estimation method |
| CN117333059B (en) * | 2023-09-28 | 2024-04-30 | 北京工商大学 | Warehouse picking path time estimation method |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113361739B (en) | 2024-04-12 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108492068B (en) | Method and device for path planning | |
| CN110371548B (en) | Goods warehousing method and device | |
| CN108734559B (en) | Order processing method and device | |
| CN110348771B (en) | Method and device for order grouping of orders | |
| CN111553548B (en) | Goods picking method and device | |
| CN110069579A (en) | Fence method of partition and device | |
| US20210312359A1 (en) | Method and device for scheduling automated guided vehicle | |
| CN111461383A (en) | Method and device for planning distribution path | |
| CN113128743B (en) | Goods picking path planning method and device | |
| CN111044062B (en) | Path planning and recommending method and device | |
| CN113128821A (en) | Method and device for determining task | |
| CN110871980B (en) | Storage classification method and device | |
| CN113361739B (en) | Method and device for generating picking path | |
| CN107085754B (en) | Information output method and device | |
| CN113255950B (en) | Method and device for optimizing logistics network | |
| CN113222205A (en) | Path planning method and device | |
| CN113762674B (en) | Order distribution method and device | |
| CN115099865A (en) | Data processing method and device | |
| CN110276508A (en) | Method and apparatus for distributing mission bit stream | |
| CN113379173A (en) | Method and apparatus for labeling warehouse goods | |
| CN112785213A (en) | Method and device for building warehouse goods picking order | |
| CN112926907A (en) | Warehouse inventory layout method and device | |
| CN113538080A (en) | Task list splitting method and device | |
| CN113743604A (en) | Method and device for searching neural network structure and identifying target | |
| CN111144601A (en) | Path planning method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |