Abstract
AbstractThis paper studies the multi-objective permutation flow shop scheduling problem (PFSP) with setup times. Firstly, the mathematical model of multi-objective PFSP with setup time is established, then based on the theory of Pareto, Genetic algorithm and Variable Neighborhood Search, a new hybrid algorithm is proposed, named as Multiple Objective Hybrid Genetic algorithm (MOHGA). Finally, a set of benchmark instances with different scales are used to evaluate the performance of MOHGA. Experimental results show that the MOHGA obtains some solutions better than those previously reported in the literature, which reveals that the proposed MOHGA is an effective approach for the optimization of multi-objective PFSP with setup time.KeywordsPermutation flow shop schedulingSetup timesMulti-objective
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