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...

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Detalhes bibliográficos
Autores: Yuichi Nagata, Soler Fernández, David
Formato: artículo
Fecha de publicación:2012
País:España
Recursos: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
Acesso em linha:https://riunet.upv.es/handle/10251/36442
Access Level:acceso abierto
Palavra-chave:Asymmetric traveling salesman problem
Crossover operator
Genetic algorithm
Metaheuristics
Combinatorial optimization problems
Optimal solutions
Real-world problem
Combinatorial optimization
Heuristic methods
MATEMATICA APLICADA
Descrição
Resumo: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.