Strategic Route Planning: An Adaptive BR-Heuristic for Multi-depot Logistics
[EN] The multiple traveling salesman problem (mTSP) is an extension of the well-known traveling salesman problem (TSP), requiring multiple agents to visit a set of nodes and return to their respective depot. This problem finds wide-ranging applications in robotics, transportation and networking, amo...
| Autores: | , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2025 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:dnet:riunet______::95c37e97cbde86ba56654dcd6a129377 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/235792 |
| Access Level: | acceso abierto |
| Palabra clave: | Multiple traveling salesman problem Bias-randomizatio |
| Sumario: | [EN] The multiple traveling salesman problem (mTSP) is an extension of the well-known traveling salesman problem (TSP), requiring multiple agents to visit a set of nodes and return to their respective depot. This problem finds wide-ranging applications in robotics, transportation and networking, among other domains. Moreover, it can be readily extended to a vehicle routing problem (VRP) by introducing extra constraints. This article presents a hybrid method for addressing the multi-depot closed path mTSP by integrating a bias-randomized heuristic with iterative local search (ILS). Furthermore, this algorithm is enhanced with a self-tuning mechanism, eliminating the need for timeconsuming fine-tuning processes. The results provided by this algorithm with a different number of depots are analyzed. |
|---|