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

摘要： 为解决低碳策略下多目标柔性作业车间调度问题,在深入分析柔性作业车间多目标调度研究现状和不足的基础上,结合基于设备状态—能耗曲线的低碳策略,提出包括能源消耗、最大完工时间、加工成本和成本加权加工质量的多目标柔性作业调度模型。针对上述模型,设计了基于血缘变异的改进非支配排序遗传算法,该算法根据计算交叉染色体的血缘关系确定变异率,优化了交叉和变异策略,解决了算法的早熟问题。针对具体实例,构建了调度模型和算法,计算结果验证了算法的可行性和有效性。

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