Multiobjective solution of the uncapacitated plant location problem
In this paper we consider the discrete multiobjective uncapacitated plant location problem. We present an exact and an approximate approach to obtain the set of non-dominated solutions. The two approaches resort to dynamic programming to generate in an efficient way the non-dominated solution sets....
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2003 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/26029 |
| Acceso en línea: | http://grupo.us.es/gpb97/curri_sevilla/doc/ejor_elena.pdf http://hdl.handle.net/11441/26029 https://doi.org/10.1016/S0377-2217(02)00223-0 |
| Access Level: | acceso abierto |
| Palabra clave: | Multiobjective combinatorial optimization Discrete location problems Dynamic programming |
| Sumario: | In this paper we consider the discrete multiobjective uncapacitated plant location problem. We present an exact and an approximate approach to obtain the set of non-dominated solutions. The two approaches resort to dynamic programming to generate in an efficient way the non-dominated solution sets. The solution methods that solve the problems associated with the generated states are based on the decomposition of the problem on two nested subproblems. We define lower and upper bound sets that lead to elimination tests that have shown to have a high performance. Computational experiments on a set of test problems show the good performance of the proposal. |
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