Abstract: Considering the problem of the multi-objective constrained flexible job-shop,the NSGA-Ⅱalgorithm based on hybrid mutation operator is proposed.In view of NSGA-II algorithm being prone to premature convergence,poisson average and gaussian operators are introduced to improve the global and local optimization ability of the algorithm.The optimal scheme is selected from the set of pareto solutions by adopting the strategy of FAHP-IEVM,which is the combination of subjective and objective evaluation method. The modified algorithm is tested and compared by a series of ZDT test functions.The results show that the convergence and diversity of the revised algorithm are improved obviously.The effectiveness of the algorithm's optimization ability,the efficiency of the running time and the rationality of the decision algorithm FAHP-IEVM are verified by an example simulation.

Key words: multi-objective optimization, NSGA-Ⅱ, mixed mutation operator, FAHP-IEVM, flexible work shop