The bi-criteria scheduling problem optimization model in a real-life flow shop with setup times was built, while the similarity of jobs were considered. The case study differs from the conventional scheduling problems. A modified genetic local search algorithm to minimize makespan and maximum tardiness was proposed. Two new neighborhood structures based on the problem-concerned knowledge were defined, and were used in the local search procedure to improve efficiency of optimization. The performance of this algorithm was compared with two multi-objective genetic local search algorithms proposed in the literature, and the simulation experiment shows that the scheduling model and proposed algorithm are relatively effective.
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