考虑工人负荷的多目标流水车间优化调度

Multi-objective flow shop optimal scheduling considering worker′s load

针对流水车间工人负荷不平衡的现象,构建了工件总延误时间和工人作业分配标准差最小化的双目标优化调度模型。设计了基于两段式染色体编码的NSGA-Ⅱ算法,获得了模型的Pareto最优解集。引入两种嵌入启发式规则:交货期最接近(EDD)规则和加工时间最短(SPT)规则,形成了NSGA-Ⅱ-EDD和NSGA-Ⅱ-SPT两种对比情境。算例分析表明:NSGA-Ⅱ算法的Pareto解的平均个数N、Pareto前沿解误差比ER、Pareto前沿解空间评价指标S、Pareto前沿跨度K比NSGA-Ⅱ-EDD和NSGA-Ⅱ-SPT的性能好,在算法运算时间T上性能较差。

To solve the problem of workers’load imbalance in the flow shop scheduling,a dual-objective optimization scheduling model is proposed in this paper with the minimum delay time and the workers’workload standard deviation.A NSGA-Ⅱbased on two-gene chromosome coding is designed to obtain Pareto-optimal solutions.Two embedded heuristic rules,the earliest due date(EDD)rule and the shortest processing time(SPT)rule,are introduced together with NSGA-Ⅱto form the NSGA-Ⅱ-EDD and NSGA-Ⅱ-SPT for comparison.Computation experimental analysis shows that NSGA-Ⅱperforms better in case of evaluation indexes with the average non-dominated solutions N,error ratio ER,spacing evaluation index S and Pareto front span K,but is worse in operation time T.