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| Autores principales: | , , , , , |
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| Formato: | Preprint |
| Publicado: |
2023
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2303.03156 |
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| _version_ | 1866916145413488640 |
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| author | Baltussen, T. M. J. T. Goutham, M. Menon, M. Garrow, S. G. Santillo, M. Stockar, S. |
| author_facet | Baltussen, T. M. J. T. Goutham, M. Menon, M. Garrow, S. G. Santillo, M. Stockar, S. |
| contents | Autonomous mobile robots enable increased flexibility of manufacturing systems. The design and operating strategy of such a fleet of robots requires careful consideration of both fixed and operational costs. In this paper, a Monte-Carlo Tree Search (MCTS)-based metaheuristic is developed that guides a Branch & Bound (B&B) algorithm to find the globally optimal solution to the Fleet Size and Mix Vehicle Routing Problem with Time Windows (FSMVRPTW).The metaheuristic and exact algorithms are implemented in a parallel hybrid optimization algorithm where the metaheuristic rapidly finds feasible solutions that provide candidate upper bounds for the B&B algorithm. The MCTS additionally provides a candidate fleet composition to initiate the B&B search. Experiments show that the proposed approach results in significant improvements in computation time and convergence to the optimal solution. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2303_03156 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | A Parallel Monte-Carlo Tree Search-Based Metaheuristic For Optimal Fleet Composition Considering Vehicle Routing Using Branch & Bound Baltussen, T. M. J. T. Goutham, M. Menon, M. Garrow, S. G. Santillo, M. Stockar, S. Systems and Control Autonomous mobile robots enable increased flexibility of manufacturing systems. The design and operating strategy of such a fleet of robots requires careful consideration of both fixed and operational costs. In this paper, a Monte-Carlo Tree Search (MCTS)-based metaheuristic is developed that guides a Branch & Bound (B&B) algorithm to find the globally optimal solution to the Fleet Size and Mix Vehicle Routing Problem with Time Windows (FSMVRPTW).The metaheuristic and exact algorithms are implemented in a parallel hybrid optimization algorithm where the metaheuristic rapidly finds feasible solutions that provide candidate upper bounds for the B&B algorithm. The MCTS additionally provides a candidate fleet composition to initiate the B&B search. Experiments show that the proposed approach results in significant improvements in computation time and convergence to the optimal solution. |
| title | A Parallel Monte-Carlo Tree Search-Based Metaheuristic For Optimal Fleet Composition Considering Vehicle Routing Using Branch & Bound |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2303.03156 |