柔性作业车间生产与能耗协同优化决策方法

针对多目标约束柔性作业车间问题,提出基于混合变异算子的NSGA-Ⅱ(Non-dominated Sorted Genetic Algorithm-Ⅱ)算法。针对NSGA-Ⅱ易早熟收敛不足的问题,分别引入泊松、平均以及高斯算子来提高算法前中后期的全局以及局部寻优能力。采用模糊层次分析—改进的熵权法(FAHP-IEVM)主客观相结合的决策方法,从多组最优解集中筛选出最优方案。通过ZDT系列测试函数对改进的算法进行测试分析对比,结果表明改进算法的收敛性和多样性指标都有明显提高。最后通过算例仿真对比分析验证了算法寻优能力及计算效率的有效性和决策方法FAHP-IEVM的合理性。

Collaborative Optimization of Production and Energy Consumption in Flexible Workshop

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.