A hybrid evolutionary approach for multicriteria optimization problems: Application to the flow shop

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Abstract

The resolution of workshop problems such as the Flow Shop or the Job Shop has a great importance in many industrial areas. The criteria to optimize are generally the minimization of the makespan or the tardiness. However, few are the resolution approaches that take into account those different criteria simultaneously. This paper presents an approach based on hybrid genetic algorithms adapted to the multicriteria case. Several strategies of selection and diversity maintaining are presented. Their performances are evaluated and compared using different benchmarks. A parallel model is also proposed and implemented for the hybrid metaheuristic. It allows to increase the population size and the number of generations, and then leads to better results.

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Talbi, E. G., Rahoual, M., Mabed, M. H., & Dhaenens, C. (2001). A hybrid evolutionary approach for multicriteria optimization problems: Application to the flow shop. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1993, pp. 416–428). Springer Verlag. https://doi.org/10.1007/3-540-44719-9_29

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