A Novel Parallel Ant Colony Optimization Algorithm for Warehouse Path Planning
In order to improve the working efficiency of automated guided vehicles (AGVs) and the processing efficiency of fulfilling orders in intelligent warehouses, a novel parallel ant colony optimization algorithm for warehouse path planning is proposed. Through the interaction of pheromones among multipl...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
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| Series: | Journal of Control Science and Engineering |
| Online Access: | http://dx.doi.org/10.1155/2020/5287189 |
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| _version_ | 1832550540605652992 |
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| author | Junqi Yu Ruolin Li Zengxi Feng Anjun Zhao Zirui Yu Ziyan Ye Junfeng Wang |
| author_facet | Junqi Yu Ruolin Li Zengxi Feng Anjun Zhao Zirui Yu Ziyan Ye Junfeng Wang |
| author_sort | Junqi Yu |
| collection | DOAJ |
| description | In order to improve the working efficiency of automated guided vehicles (AGVs) and the processing efficiency of fulfilling orders in intelligent warehouses, a novel parallel ant colony optimization algorithm for warehouse path planning is proposed. Through the interaction of pheromones among multiple subcolonies, the coevolution of multiple subcolonies is realized and the operational capability of the algorithm is improved. Then, a multiobjective function with the object of the shortest path and the minimum number of turns of the AGV is established. And the path satisfying this objective function is obtained by the proposed algorithm. In addition, the path is further smoothed by reducing the number of intermediate nodes. The results show that the stability and convergence rate of the algorithm are faster and more stable, compared to other algorithms, in generating paths for different complexity maps. The smoothing treatment of the path significantly reduces the number of turns and the path length in the AGV driving process. |
| format | Article |
| id | doaj-art-291f406f453e4529a32004c7d8d86775 |
| institution | Kabale University |
| issn | 1687-5249 1687-5257 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Control Science and Engineering |
| spelling | doaj-art-291f406f453e4529a32004c7d8d867752025-02-03T06:06:26ZengWileyJournal of Control Science and Engineering1687-52491687-52572020-01-01202010.1155/2020/52871895287189A Novel Parallel Ant Colony Optimization Algorithm for Warehouse Path PlanningJunqi Yu0Ruolin Li1Zengxi Feng2Anjun Zhao3Zirui Yu4Ziyan Ye5Junfeng Wang6Xi’an University of Architecture and Technology, Xi’an 710055, ChinaXi’an University of Architecture and Technology, Xi’an 710055, ChinaXi’an University of Architecture and Technology, Xi’an 710055, ChinaXi’an University of Architecture and Technology, Xi’an 710055, ChinaXi’an University of Architecture and Technology, Xi’an 710055, ChinaXi’an University of Architecture and Technology, Xi’an 710055, ChinaHuafa Architectural Design Consulting Ltd., Zhuhai 519000, ChinaIn order to improve the working efficiency of automated guided vehicles (AGVs) and the processing efficiency of fulfilling orders in intelligent warehouses, a novel parallel ant colony optimization algorithm for warehouse path planning is proposed. Through the interaction of pheromones among multiple subcolonies, the coevolution of multiple subcolonies is realized and the operational capability of the algorithm is improved. Then, a multiobjective function with the object of the shortest path and the minimum number of turns of the AGV is established. And the path satisfying this objective function is obtained by the proposed algorithm. In addition, the path is further smoothed by reducing the number of intermediate nodes. The results show that the stability and convergence rate of the algorithm are faster and more stable, compared to other algorithms, in generating paths for different complexity maps. The smoothing treatment of the path significantly reduces the number of turns and the path length in the AGV driving process.http://dx.doi.org/10.1155/2020/5287189 |
| spellingShingle | Junqi Yu Ruolin Li Zengxi Feng Anjun Zhao Zirui Yu Ziyan Ye Junfeng Wang A Novel Parallel Ant Colony Optimization Algorithm for Warehouse Path Planning Journal of Control Science and Engineering |
| title | A Novel Parallel Ant Colony Optimization Algorithm for Warehouse Path Planning |
| title_full | A Novel Parallel Ant Colony Optimization Algorithm for Warehouse Path Planning |
| title_fullStr | A Novel Parallel Ant Colony Optimization Algorithm for Warehouse Path Planning |
| title_full_unstemmed | A Novel Parallel Ant Colony Optimization Algorithm for Warehouse Path Planning |
| title_short | A Novel Parallel Ant Colony Optimization Algorithm for Warehouse Path Planning |
| title_sort | novel parallel ant colony optimization algorithm for warehouse path planning |
| url | http://dx.doi.org/10.1155/2020/5287189 |
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