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A Comparison between Two Modified NSGA-II Algorithms for Solving the Multi-objective Flexible Job Shop Scheduling Problem
Universal Journal of Applied Mathematics
Many evolutionary algorithms have been used to solve multi-objective scheduling problems. NSGA-II is one of them that is based on the Pareto optimality concept and generally obtains good results. However, it is possible to improve its performance with some modifications. In this paper, two modified NSGA-II algorithms have been suggested for solving the multi-objective flexible job shop scheduling problem. The neighborhood structures defined for the problem are integrated into the algorithms todoi:10.13189/ujam.2018.060302 fatcat:f2vepnbj4fd6bmrcu4xtvw4jk4