Búsqueda tabú multiobjetivo con Enteros-mixtos y punto de referencia

Beausoleil, Ricardo p.; Beausoleil, Ricardo p.

doi:10.15517/rmta.v1i25.32234

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Revista de Matemática Teoría y Aplicaciones

versión impresa ISSN 1409-2433

Rev. Mat vol.25 no.1 San José ene./jun. 2018

http://dx.doi.org/10.15517/rmta.v1i25.32234

Artículos

Búsqueda tabú multiobjetivo con Enteros-mixtos y punto de referencia

Multiobjective tabu search with mixedIntegers and reference point

Ricardo p. Beausoleil¹

^¹Matemática Interdiciplinaria, ICIMAF, La Habana, Cuba. E-Mail: rbeau@icimaf.cu, rbeau3105@gmail.com

Resumen

En este trabajo presentamos un enfoque de Búsqueda Tabú independiente del dominio para problemas con múltiples objetivos y variables mixtas (enteras y reales). En el mismo investigamos dos aspectos: la independencia del dominio y la aplicabilidad en la optimización práctica, para ello nos centramos en problemas que se encuentran frecuentemente en el mundo real, como son los problemas de redes logísticas (por ejemplo: problemas de redes de distribución con múltiples etapas, localización asignación, tablas de tiempo); también investigamos su desempeño sobre problemas clásicos como cubri-miento de conjuntos, particionamiento de conjunto, mochila multidimensional y camino más corto. Todos los problemas considerados son de la clase NP-duros, con gran número de variables, conteniendo un número de restricciones heterogéneas, presentando un reto para hallar soluciones factibles.

Palabras clave: múltiples objetivos; metaheurísticas; búsqueda tabú

Abstract

In this work we present a domain-independent Tabu Search approach for multiobjective optimization with mixed-integer variables. In this we investigate two aspects: domain-independence and applicability in optimization practice and focus our attention in problems that appear frequently in the real world, like logistic network (for example: multi-stage distribution networks problems, location-allocation problems, time-tabling problems); however, other classical problems were investigated, like: coverage set problem, partitioning set problem, multidimentional knapsack problem and shortest path problem. All these problems belong to the NP-hard class, with a great number of decision variables, containing a great number of heterogeneous constrains, presenting a challenge to find feasible solutions.

Keywords: multiple objetives; metaheuristics; tabu search

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Recibido: 10 de Noviembre de 2016; Revisado: 22 de Septiembre de 2017; Aprobado: 17 de Octubre de 2017

Este es un artículo publicado en acceso abierto bajo una licencia Creative Commons