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Descripción
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| This dissertation deals with the use of quantitative methods (more specifically, metaheuristic techniques) for analysing locating problems in reverse logistics, in general, and two problems proposed by the author, in particular. A methodology is proposed, being based on the utilisation of metaheuristic techniques, the solutions structure for the metaheuristc (composed of arrays) and a solving tool which comprises a metaheuristic, a modeller and a solver to quickly solve continuous linnear models. Among the metaheuristic techniques that can be found in the literature, two of them have been chosen to test the validity of the proposed approach: the genetic algorithms and the scatter search. As a case study, two especially interesting problems have been identified. First, the problem consisting in locating plants for recoverying light fragmented waste from end of life vehicles (dynamic nature); and, second, the problem consisting in locating a single treatment plant and the necessary transfer centers for recoverying the waste from a particular region (dynamic and stochastic nature). Both problems are estated altoghether with their corresponding models:MPMCFLP} (Multiple Period Multiple Capacitated Facility Location Problem) and STPNTCLP (Single Treatment Plant and Necessary Transfer Centers Location Problem). The metodology and the proposed metaheuristic techniques with their particular adaptations have been implemented in a software tool. This tool has been developed in three independent layers: a Visual Basic application to configure and run the metaheuristic technique, AIMMS as a modeler and the CPLEX solver. The results for different instances of the SPNTPCLP problem suggest the validity of this approach, mainly for the case of the scatter search. | |
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Internacional
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No |
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ISBN
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Tipo de Tesis
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Doctoral |
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Calificación
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Sobresaliente cum laude |
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Fecha
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13/03/2008 |