计算机应用研究2017，Vol.34Issue(12)：3623-3627,3646,6.DOI:10.3969/j.issn.1001-3695.2017.12.023
求解多目标作业车间调度问题的混合变异杂草优化算法
Composite mutation invasive weed optimization algorithm for multi-objective Job-Shop scheduling problem
摘要
Abstract
To solve multi-objective Job-Shop scheduling problem,this paper proposed a composite mutation invasive weed optimization algorithm.The method adopted a fitness calculating method of Euclidean approach degree to help population move towards the Pareto front.In each generation of the evolving process,the algorithm presented a fast non-dominated sorting approach to improve the efficiency of constructing Pareto optimal solutions.It integrated the global best solution of evolutionary population into updating Pareto optimal solutions instantly to enhance performance of the optimization algorithm,and introduced the mutation operator to increase population diversity,avoiding being trapped in local optimum.The experimental resuits of the Benchmark instances demonstrate the effectiveness of the algorithm proposed on solving multi-objective Job-Shop scheduling problems.关键词
多目标优化/作业车间调度/入侵杂草优化算法/欧氏贴近度Key words
multi-objective optimization/Job-Shop scheduling/invasive weed optimization algorithm/Euclidean approach degree分类
信息技术与安全科学引用本文复制引用
黄霞,叶春明,曹磊..求解多目标作业车间调度问题的混合变异杂草优化算法[J].计算机应用研究,2017,34(12):3623-3627,3646,6.基金项目
国家自然科学基金资助项目(71271138) （71271138）
上海市一流学科资助项目(S1201YLXK) （S1201YLXK）
沪江基金资助项目(A14006) （A14006）
江苏省现教课题项目(48888) （48888）
江苏省高等教育科学研究“十三五”规划课题项目(16YB064) （16YB064）
