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Ingeniare. Revista chilena de ingeniería

versión On-line ISSN 0718-3305

Ingeniare. Rev. chil. ing. v.16 n.3 Arica dic. 2008

http://dx.doi.org/10.4067/S0718-33052008000300006 

 

Ingeniare. Revista chilena de ingeniería, vol. 16 Nº 3, 2008, pp. 428-437

INTRODUCCIÓN DE  ELEMENTOS DE MEMORIA EN EL MÉTODO SIMULATED ANNEALING PARA RESOLVER PROBLEMAS DE PROGRAMACIÓN MULTIOBJETIVO DE MÁQUINAS PARALELAS

 INTRODUCTION OF MEMORY ELEMENTS IN SIMULATED ANNEALING METHOD TO SOLVE MULTIOBJECTIVE PARALLEL MACHINE SCHEDULING PROBLEMS

Felipe Baesler1          Reinaldo Moraga2          Oscar Cornejo3

 

1 Departamento de Ingeniería Industrial. Universidad del Bío-Bío. Avenida Collao 1202. Concepción, Chile. E-mail: fbaesler@ubiobio.cl
2 Department of Industrial and System Engineering. University of Northern Illinois. Dekalb, USA. E-mail: moraga@ceet.niu.edu
3 Facultad de Ingeniería. Universidad Católica de la Santísima Concepción. Concepción, Chile. E-mail: ocornejo@ucsc.cl



RESUMEN 

El presente artículo introduce una variante de la metaheurística simulated annealing, para la resolución de problemas de optimización multiobjetivo. Este enfoque se demonina MultiObjective Simulated Annealing with Random Trajectory Search, MOSARTS. Esta técnica agrega al algoritmo Simulated Annealing elementos de memoria de corto y largo plazo para realizar una búsqueda que permita balancear el esfuerzo entre todos los objetivos involucrados en el problema. Los resultados obtenidos se compararon con otras tres metodologías en un problema real de programación de máquinas paralelas, compuesto por 24 trabajos y 2 máquinas idénticas. Este problema corresponde a un caso de estudio real de la industria regional del aserrío. En los experimentos realizados, MOSARTS se comportó de mejor manera que el resto de la herramientas de comparación, encontrando mejores soluciones en términos de dominancia y dispersión. 

Palabras clave: Simulated Annealing, multiobjetivo, programación de la producción.


ABSTRACT

This paper introduces a variant of the metaheuristic simulated annealing, oriented to solve multiobjective optimization problems. This technique is called MultiObjective Simulated Annealing with Random Trajectory Search (MOSARTS). This technique incorporates short an long term memory concepts to Simulated Annealing in order to balance the search effort among all the objectives involved in the problem. The algorithm was tested against three different techniques on a real life parallel machine scheduling problem, composed of 24 jobs and two identical machines. This problem represents a real life case study of the local sawmill industry. The results showed that MOSARTS behaved much better than the other methods utilized, because found better solutions in terms of dominance and frontier dispersion.

Keywords: Simulated Annealing, multiobjective, scheduling.

 

AGRADECIMIENTOS

Este trabajo fue financiado por los proyectos 052011 3/R de la Dirección de Investigación de la Universidad del Bío-Bío, Concepción-Chile y DIN 10/2005 de la Dirección de Investigación Universidad Católica de la Santísima Concepción, Concepción-Chile.


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Recibido 28 de junio de 2005, aceptado 29 de abril de 2008

 

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