Multi-objective scheduling on two dedicated processors
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We study a multi-objective scheduling problem on two dedicated processors. The aim is to minimize simultaneously the makespan, the total tardiness and the total completion time. This NP-hard problem requires the use of well-adapted methods. For this, we adapted genetic algorithms to multiobjective case. Three methods are presented to solve this problem. The first is aggregative, the second is Pareto and the third is the NSGA-II algorithm. We proposed some adapted lower bounds for each criterion to evaluate the quality of the found results on a large set of instances. The obtained results show the effectiveness of the proposed algorithms.
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