南京理工大学学报（自然科学版）2017，Vol.41Issue(4)：494-502,9.DOI:10.14177/j.cnki.32-1397n.2017.41.04.015
基于改进遗传算法的多目标柔性作业车间节能调度问题
Multi-objective flexible job shop energy-saving scheduling problem based on improved genetic algorithm
摘要
Abstract
To reduce the energy consumption in flexible job shop scheduling,by analyzing the current research status and insufficiency,the makespan,power consumption of machine and the comfort level of employee are supposed as multi-objectives function for flexible job shop scheduling problem(FJSP).An improved genetic algorithm is proposed to optimize this problem.The weighting method is used to initialize the population in order to obtain better solution,meanwhile the total fitness value is obtained by a fast decoding method.The modified crossover and mutation operations are used to avoid creating the illegal solution.The elitism strategy is used to keep good genes.The efficiency and quality of solution can be improved by using the proposed improved genetic algorithm.Simulation tests are done to verify the effectiveness of the proposed improved genetic algorithm.关键词
改进遗传算法/多目标/柔性作业车间调度/舒适度/节能调度Key words
improved genetic algorithm/multi-objective/flexible job shop scheduling/comfort/energy-saving scheduling分类
信息技术与安全科学引用本文复制引用
王雷,蔡劲草,石鑫..基于改进遗传算法的多目标柔性作业车间节能调度问题[J].南京理工大学学报（自然科学版）,2017,41(4):494-502,9.基金项目
国家自然科学基金(51305001) （51305001）
安徽省自然科学基金(1708085ME129) （1708085ME129）
安徽省高校优秀青年人才支持计划重点项目(gxyqZD2016125) （gxyqZD2016125）
安徽省科技计划项目(1604a0902183) （1604a0902183）
