New multi-objective method to solve reentrant hybrid flow shop scheduling problem

Frédéric Dugardin, Farouk Yalaoui and Lionel Amodeo

European Journal of Operational Research, 2010, vol. 203, issue 1, 22-31

Abstract: This paper focuses on the multi-objective resolution of a reentrant hybrid flow shop scheduling problem (RHFS). In our case the two objectives are: the maximization of the utilization rate of the bottleneck and the minimization of the maximum completion time. This problem is solved with a new multi-objective genetic algorithm called L-NSGA which uses the Lorenz dominance relationship. The results of L-NSGA are compared with NSGA2, SPEA2 and an exact method. A stochastic model of the system is proposed and used with a discrete event simulation module. A test protocol is applied to compare the four methods on various configurations of the problem. The comparison is established using two standard multi-objective metrics. The Lorenz dominance relationship provides a stronger selection than the Pareto dominance and gives better results than the latter. The computational tests show that L-NSGA provides better solutions than NSGA2 and SPEA2; moreover, its solutions are closer to the optimal front. The efficiency of our method is verified in an industrial field-experiment.

Keywords: Reentrant; shops; Scheduling; Lorenz; dominance; Equitable; dominance; Multi-criteria; optimization; Genetic; algorithm (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:203:y:2010:i:1:p:22-31

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