Beam-ACO for the travelling salesman problem with time windows
The travelling salesman problem with time windows is a difficult optimization problem that arises, for example, in logistics. This paper deals with the minimization of the travel cost. For solving this problem, this paper proposes a Beam-ACO algorithm, which is a hybrid method that combines ant colo...
| Autores: | , |
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| Tipo de recurso: | informe técnico |
| Fecha de publicación: | 2009 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/88010 |
| Acceso en línea: | https://hdl.handle.net/2117/88010 |
| Access Level: | acceso abierto |
| Palabra clave: | Ant colony optimization Beam search Hybridization Travelling salesman Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica |
| Sumario: | The travelling salesman problem with time windows is a difficult optimization problem that arises, for example, in logistics. This paper deals with the minimization of the travel cost. For solving this problem, this paper proposes a Beam-ACO algorithm, which is a hybrid method that combines ant colony optimization with beam search. In general, Beam-ACO algorithms heavily rely on accurate and computationally inexpensive bounding information for differentiating between partial solutions. This work uses stochastic sampling as a useful alternative. An extensive experimental evaluation on seven benchmark sets from the literature shows that the proposed Beam-ACO algorithm is currently a state-of-the-art technique for the travelling salesman problem with time windows under travel-cost optimization. |
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