摘要
针对再制造加工过程中作业时间的不确定性以及现行车间调度问题中多目标并行的特点,以三角模糊数描述再制造加工车间作业时间的不确定性,建立以完工时间、加工成本、设备负载平衡和加工能耗为目标的再制造加工车间调度模型,并提出一种基于多种群协同进化的混合人工鱼群算法对模型进行求解.该算法采用多种群协同进化的思想提高单种群混合人工鱼群算法的搜索能力,并考虑对多目标再制造加工车间调度问题的适用性,最后以个体分散程度为指标更新Pareto解集中的最优解.仿真实验验证了所提出方法的可行性.
In view of the uncertainty of remanufacturing processing time and multi-objective parallelism that exists in the job-shop scheduling problems. A multi-objective scheduling model of remanufacturing job-shop considering completion time, cost, load balancing and energy consumption is established based on triangular fuzzy operation time of work-piece.Besides, a multi-population hybrid artificial fish swarm algorithm is applied to solve the proposed model. In this algorithm,a multi-population co-evolution strategy is used to improve the efficiency of the algorithm. And then, the Pareto solution set is updated with individual dispersion as the evaluation criterion. Finally, one case of the remanufacturing job-shop scheduling problem is presented to illustrate the feasibility of the proposed method.
作者
郭钧
钟精诚
杜百岗
吴锐
李益兵
GUO Jun;ZHONG Jing-cheng;DU Bai-gang;WU Rui;LI Yi-bing(School of Mechanical and Electrical Engineering,Wuhan University of Technology.Wuhan 430070,China)
出处
《控制与决策》
EI
CSCD
北大核心
2020年第6期1497-1504,共8页
Control and Decision
基金
国家自然科学基金项目(51705386)
中央高校基本科研业务费专项资金项目(2018-IVB-010).
关键词
再制造加工车间调度
模糊作业时间
多目标优化
混合人工鱼群算法
多种群协同
remanufacturing reprocessing shop scheduling
fuzzy operation time
multi-objective optimization
hybrid artificial fish swarm algorithm
multi-population co-evolution
