东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2011, Vol. 32 ›› Issue (2): 183-187.DOI: -

• 论著 • 上一篇    下一篇

求解交货期可变动态调度问题的差分进化算法

刘黎黎;王诗元;汪定伟;   

  1. 东北大学信息科学与工程学院;东北大学流程工业综合自动化教育部重点实验室;
  • 收稿日期:2013-06-19 修回日期:2013-06-19 发布日期:2013-04-04
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家自然科学基金重点资助项目(70931001,70771021,70721001);国家自然科学基金青年基金资助项目(61004121);国家自然科学基金创新群体项目(60821063);;

A differential evolution algorithm for dynamic scheduling with variable delivery dates

Liu, Li-Li (1); Wang, Shi-Yuan (1); Wang, Ding-Wei (2)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110819, China; (2) Key Laboratory of Integrated Automation of Process Industry, Ministry of Education, Northeastern University, Shenyang 110819, China
  • Received:2013-06-19 Revised:2013-06-19 Published:2013-04-04
  • Contact: Liu, L.-L.
  • About author:-
  • Supported by:
    -

RichHTML

0

PDF (PC)

643

摘要： 针对差分进化算法求解动态优化问题时存在多样性缺失、寻优效率低的问题,提出一种多种群差分进化算法,将这种用于求解连续解空间优化问题的进化算法应用于顺序编码的动态调度问题求解中.该算法利用随机键编码表示法将连续位置向量转化为顺序编码.提出自组织多种群策略,将种群按动态空间特征自动分成主种群与子种群;由主种群不断探索峰值所在区域,从主种群分离出来的子种群负责在这些有效区域进行开发,并对子种群规模进行自适应调整,以加快算法寻优速度并节省计算资源.算法应用于交货期可变动态调度问题中,取得了满意结果.

关键词: 差分进化, 多种群, 动态调度, 自组织

Abstract: Diversity loss and low optimizing efficiency are the two problems to be solved for the differential evolution (DE) algorithm in dynamic environment. A multi-population DE algorithm usually applied to the space optimization of continuous solution is proposed for the solution of dynamic scheduling problem with sequential coding, where the representative method using random keys for coding is introduced to transform the continuous position vectors into sequential coding. A self-organizing multi-population strategy is then set out to divide the population into parent population and child population, which is separated automatically from the parent one in accordance to their dynamic spatial characteristics. With the parent population in uninterrupted search of the regions where the peaks take place, the child population is assigned to exploit the useful regions further with adaptive adjustment done for its size, thus expediting the optimizing speed of the algorithm with computing resource saved. The algorithm proposed has been applied to the dynamic scheduling with variable delivery date, and a satisfactory result is gained.

中图分类号: