A new genetic algorithm for the asymmetric traveling salesman problem
The asymmetric traveling salesman problem (ATSP) is one of the most important combinatorial optimization problems. It allows us to solve, either directly or through a transformation, many real-world problems. We present in this paper a new competitive genetic algorithm to solve this problem. This al...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2012 |
| País: | España |
| Institución: | Universitat Politècnica de València (UPV) |
| Repositorio: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglés |
| OAI Identifier: | oai:riunet.upv.es:10251/36442 |
| Acceso en línea: | https://riunet.upv.es/handle/10251/36442 |
| Access Level: | acceso abierto |
| Palabra clave: | Asymmetric traveling salesman problem Crossover operator Genetic algorithm Metaheuristics Combinatorial optimization problems Optimal solutions Real-world problem Combinatorial optimization Heuristic methods MATEMATICA APLICADA |
| Sumario: | The asymmetric traveling salesman problem (ATSP) is one of the most important combinatorial optimization problems. It allows us to solve, either directly or through a transformation, many real-world problems. We present in this paper a new competitive genetic algorithm to solve this problem. This algorithm has been checked on a set of 153 benchmark instances with known optimal solution and it outperforms the results obtained with previous ATSP heuristic methods. © 2012 Elsevier Ltd. All rights reserved. |
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