计算机应用研究2017，Vol.34Issue(5)：1337-1341,5.DOI:10.3969/j.issn.1001-3695.2017.05.013
基于模糊物元模型的高维多目标FJSP研究
High-dimensional multi-objective FJSP research based on fuzzy matter-element model
摘要
Abstract
In order to solve high-dimensional multi-objective flexible Job-Shop scheduling problem,this paper proposed a fuzzy particle swarm optimization algorithm which was based on fuzzy matter element model and particle swarm algorithm.The proposed algorithm adopted the Euclid approach degree between the fuzzy matter element and the standard fuzzy matter element as fitness value to lead the evolution of particle swarm optimization algorithm,and introduced an external storage with constrained capacity to reserve the optimal Pareto non-dominated solutions.Besides,this paper constructed high-dimensional multi-objective flexible Job-Shop scheduling model,where makespan,total machine load,cost,maximum machine load and crudy were all concerned.The results of simulation based on Kacem benchmark problem and actual production problem show that the proposed algorithm has good convergence and can also achieve Pareto optimal solution with an ideal uniformity,it can solve high dimension multi-objective flexible Job-Shop scheduling problem effectively.关键词
模糊物元模型/粒子群算法/梯形隶属度函数/欧氏贴近度Key words
fuzzy matter-element model/particle swarm optimization algorithm/trapezoidal subordinate function/Euclid approach degree分类
信息技术与安全科学引用本文复制引用
黄利福,梁工谦,董仲慧..基于模糊物元模型的高维多目标FJSP研究[J].计算机应用研究,2017,34(5):1337-1341,5.基金项目
国家自然科学基金资助项目(U1404702) （U1404702）
