东北大学学报（自然科学版）

东北大学学报(自然科学版) ›› 2010, Vol. 31 ›› Issue (12): 1697-1700.DOI: -

• 论著 • 上一篇    下一篇

改进的差分进化算法在工作分配中的应用

吴沛锋;高立群;邹德旋;   

  1. 东北大学信息科学与工程学院;
  • 收稿日期:2013-06-20 修回日期:2013-06-20 出版日期:2010-12-15 发布日期:2013-06-20
  • 通讯作者: -
  • 作者简介:-
  • 基金资助:
    国家自然科学基金资助项目(60674021)

Application of improved differential evolution algorithm to task assignment

Wu, Pei-Feng (1); Gao, Li-Qun (1); Zou, De-Xuan (1)   

  1. (1) School of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2013-06-20 Revised:2013-06-20 Online:2010-12-15 Published:2013-06-20
  • Contact: Zou, D.-X.
  • About author:-
  • Supported by:
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摘要： 提出了一种改进的差分进化算法(IDE)以解决工作分配.它修正了DE算法的两个重要的参数:尺度因子和交叉率.尺度因子根据所有解向量的目标函数值而自适应地调整,交叉率随着迭代次数的增加而动态地调整.通过结合这两种参数,不仅增加了候选解的多样性,还增强了本算法的解空间开发能力.实验表明,在解决工作分配上,IDE算法比其他三种DE算法具有更强的收敛性和稳定性.

关键词: 改进的差分进化算法, 工作分配问题, 差分进化算法, 尺度因子, 交叉率

Abstract: An improved differential evolution (IDE) algorithm was proposed for task assignment by modifying two important parameters of DE algorithm: scale factor and crossover rate. The scale factor is adaptively adjusted according to the objective function values of all candidate solution vectors, and the crossover rate is dynamically adjusted with the increasing of iteration steps. The combination of such two parameters is able to not only increase the diversity of candidate solutions but also enhance the develop ability of solution space of the proposed algorithm. Experimental results demonstrated that the IDE algorithm has stronger convergence and higher stability than other three DE algorithms for task assignment.

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