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

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-II based 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-II to form the NSGA-II-EDD and NSGA-II-SPT for comparison. Computation experimental analysis shows that NSGA-II performs 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. © 2021, Jilin University Press. All right reserved.