Data-Driven Robust Optimization of the Vehicle Routing Problem with Uncertain Customers
With the increasing proportion of the logistics industry in the economy, the study of the vehicle routing problem has practical significance for economic development. Based on the vehicle routing problem (VRP), the customer presence probability data are introduced as an uncertain random parameter, a...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/9064669 |
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| _version_ | 1832552891961835520 |
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| author | Jingling Zhang Yusu Sun Qinbing Feng Yanwei Zhao Zheng Wang |
| author_facet | Jingling Zhang Yusu Sun Qinbing Feng Yanwei Zhao Zheng Wang |
| author_sort | Jingling Zhang |
| collection | DOAJ |
| description | With the increasing proportion of the logistics industry in the economy, the study of the vehicle routing problem has practical significance for economic development. Based on the vehicle routing problem (VRP), the customer presence probability data are introduced as an uncertain random parameter, and the VRP model of uncertain customers is established. By optimizing the robust uncertainty model, combined with a data-driven kernel density estimation method, the distribution feature set of historical data samples can then be fitted, and finally, a distributed robust vehicle routing model for uncertain customers is established. The Q-learning algorithm in reinforcement learning is introduced into the high-level selection strategy using the hyper-heuristic algorithm, and a hyper-heuristic algorithm based on the Q-learning algorithm is designed to solve the problem. Compared with the certain method, the distributed robust model can effectively reduce the total cost and the robust conservatism while ensuring customer satisfaction. The improved algorithm also has good performance. |
| format | Article |
| id | doaj-art-0722c789738741d684d633d4c114786e |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-0722c789738741d684d633d4c114786e2025-02-03T05:57:31ZengWileyComplexity1099-05262022-01-01202210.1155/2022/9064669Data-Driven Robust Optimization of the Vehicle Routing Problem with Uncertain CustomersJingling Zhang0Yusu Sun1Qinbing Feng2Yanwei Zhao3Zheng Wang4Key Laboratory of Special Equipment Manufacturing and Advanced Processing TechnologyKey Laboratory of Special Equipment Manufacturing and Advanced Processing TechnologyKey Laboratory of Special Equipment Manufacturing and Advanced Processing TechnologyKey Laboratory of Special Equipment Manufacturing and Advanced Processing TechnologyThe State Key Laboratory of Digital Manufacturing Equipment and TechnologyWith the increasing proportion of the logistics industry in the economy, the study of the vehicle routing problem has practical significance for economic development. Based on the vehicle routing problem (VRP), the customer presence probability data are introduced as an uncertain random parameter, and the VRP model of uncertain customers is established. By optimizing the robust uncertainty model, combined with a data-driven kernel density estimation method, the distribution feature set of historical data samples can then be fitted, and finally, a distributed robust vehicle routing model for uncertain customers is established. The Q-learning algorithm in reinforcement learning is introduced into the high-level selection strategy using the hyper-heuristic algorithm, and a hyper-heuristic algorithm based on the Q-learning algorithm is designed to solve the problem. Compared with the certain method, the distributed robust model can effectively reduce the total cost and the robust conservatism while ensuring customer satisfaction. The improved algorithm also has good performance.http://dx.doi.org/10.1155/2022/9064669 |
| spellingShingle | Jingling Zhang Yusu Sun Qinbing Feng Yanwei Zhao Zheng Wang Data-Driven Robust Optimization of the Vehicle Routing Problem with Uncertain Customers Complexity |
| title | Data-Driven Robust Optimization of the Vehicle Routing Problem with Uncertain Customers |
| title_full | Data-Driven Robust Optimization of the Vehicle Routing Problem with Uncertain Customers |
| title_fullStr | Data-Driven Robust Optimization of the Vehicle Routing Problem with Uncertain Customers |
| title_full_unstemmed | Data-Driven Robust Optimization of the Vehicle Routing Problem with Uncertain Customers |
| title_short | Data-Driven Robust Optimization of the Vehicle Routing Problem with Uncertain Customers |
| title_sort | data driven robust optimization of the vehicle routing problem with uncertain customers |
| url | http://dx.doi.org/10.1155/2022/9064669 |
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