多目标置换流水车间调度的混沌杂草优化算法

发布时间：2018-03-07 21:27

  本文选题：多目标优化　切入点：置换流水车间调度　出处：《系统工程理论与实践》2017年01期 　论文类型：期刊论文

【摘要】：针对最小化最大完工时间,总流程时间及总延迟时间的多目标置换流水车间调度问题,提出一种改进的混沌杂草优化算法,该算法采用基于熵值权重的灰熵关联度适应值分配策略,引入快速非支配排序法生成外部档案,并将进化种群的更新和最优位置的混沌搜索相结合,用于维护外部档案,提升算法的寻优性能.通过与NSGA-Ⅱ算法进行OR-Library典型测试算例的对比实验,验证该算法的有效性.
[Abstract]:In order to minimize the maximum completion time, total process time and total delay time, an improved chaotic weed optimization algorithm is proposed for income job-shop scheduling problem. In this algorithm, the grey entropy correlation fitness allocation strategy based on entropy weight is adopted, and the fast non-dominated sorting method is introduced to generate external files, and the update of evolutionary population is combined with the chaotic search of optimal location to maintain the external files. To improve the performance of the algorithm, the effectiveness of the algorithm is verified by the comparison of OR-Library typical test cases with NSGA- 鈪，

本文编号：1581022