关键词: 多目标调度, 柔性作业车间, 改进非支配排序遗传算法, 低碳策略, 血缘变异

Abstract: To solve multi-objective Flexible Job-shop Scheduling Problem (FJSP) under low-carbon strategy,by analyzing the current research status and insufficiency,a multi-objective FJSP optimization model based on low-carbon strategy of equipment state-energy-consumption curve was put forward,in which the energy consumption,makespan,processing cost and cost-weighted processing quality were considered.According to above model,a modified Non-dominated Sorting Genetic Algorithm (NSGA-Ⅱ) with blood variation was designed.In this algorithm,the chromosome mutation rate was determined after calculating the blood relationship between the two cross chromosomes,the crossover and mutation strategy of NSGA-Ⅱ was optimized and the prematurity of population was overcome.The performance of the proposed model and algorithm were evaluated through a case study,and the results demonstrated the efficiency and feasibility of the proposed model and algorithm.

Key words: multi-objective scheduling, flexible job-shop, non-dominated sorting genetic algorithm, low-carbon strategy, blood variation