• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>2011 Seventh International Conference on Natural Computation >A Cooperative Dual-swarm PSO for dynamic optimization problems
【24h】

A Cooperative Dual-swarm PSO for dynamic optimization problems

机译：协同双群PSO解决动态优化问题

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Many practical applications are dynamic over time, which require optimization algorithms not only to converge to optimum as soon as possible but also to track the changing optimum. In this paper, a Cooperative Dual-swarm PSO (CDPSO) is proposed to deal with dynamic optimization problems. CDPSO adopts dual-swarm structure to keep swarm diversity and track the changing optimum. Fractional Global Best Formation technique is employed to construct artificial global bests which are potential to be better. Also an adaptive mutation operator is designed to maintain particle diversity. The experiments demonstrate that the proposed algorithm is effective and stable in dynamic environment.
机译：许多实际应用随着时间的推移是动态的，因此不仅需要优化算法尽快收敛到最佳状态，而且还需要跟踪变化的最佳状态。本文提出了一种协同双群PSO（CDPSO）来解决动态优化问题。 CDPSO采用双群结构来保持群多样性并跟踪变化的最佳状态。使用分数全球最佳形成技术来构建可能会变得更好的人为全局最佳。还设计了自适应突变算子来维持粒子多样性。实验表明，该算法在动态环境下是有效且稳定的。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号