Solving multifacility Huff location models on networks using metaheuristic and exact approaches
In this paper we consider multifacility Huff facility location problem on networks. First, we introduce a slight modification of the existing mixed integer nonlinear mathematical model and confirm its validity by using the solver for nonlinear optimization, KNITRO. Second, since the problem is NP-ha...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | España |
| Institución: | Universidad de Sevilla (US) |
| Repositorio: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/107834 |
| Acceso en línea: | https://hdl.handle.net/11441/107834 https://doi.org/10.1016/j.cor.2016.03.005 |
| Access Level: | acceso abierto |
| Palabra clave: | Location Networks Competitive location Metaheuristics Variable Neighborhood Search |
| Sumario: | In this paper we consider multifacility Huff facility location problem on networks. First, we introduce a slight modification of the existing mixed integer nonlinear mathematical model and confirm its validity by using the solver for nonlinear optimization, KNITRO. Second, since the problem is NP-hard, we develop three methods that are based on three metaheuristic principles: Variable Neighborhood Search, Simulated Annealing, and Multi-Start Local Search. Based on extensive computational experiments on large size instances (up to 800 customers and 100 potential facilities), it appears that VNS based heuristic outperforms the other two proposed methods. |
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