首页> 外文会议>International conference on swarm intelligence >Strategies to Improve Cuckoo Search Toward Adapting Randomly Changing Environment
【24h】

Strategies to Improve Cuckoo Search Toward Adapting Randomly Changing Environment

机译:改善布谷鸟搜索以适应随机变化环境的策略

获取原文

摘要

Cuckoo Search (CS) is the powerful optimization algorithm and has been researched recently. Cuckoo Search for Dynamic Environment (D-CS) has proposed and tested in dynamic environment with multi-modality and cyclically before. It was clear that has the hold capability and can find the optimal solutions in this environment. Although these experiments only provide the valuable results in this environment, D-CS not fully explored in dynamic environment with other dynamism. We investigate and discuss the find and hold capabilities of D-CS on dynamic environment with randomness. We employed the multi-modal dynamic function with randomness and applied D-CS into this environment. We compared D-CS with CS in terms of getting the better fitness. The experimental result shows the D-CS has the good hold capability on dynamic environment with randomness. Introducing the Local Solution Comparison strategy and Concurrent Solution Generating strategy help to get the hold and find capabilities on dynamic environment with randomness.
机译:布谷鸟搜索(Cuckoo Search,CS)是功能强大的优化算法,最近已经进行了研究。布谷鸟动态环境搜索(D-CS)已在动态环境中以多模式和循环方式提出并进行了测试。显然,它具有保持能力,并且可以在这种环境下找到最佳解决方案。尽管这些实验仅在这种环境下提供了有价值的结果,但在动态环境中还没有充分探索D-CS的动态性。我们研究并讨论了D-CS在动态环境下具有随机性的查找和保持功能。我们采用具有随机性的多模式动态函数,并将D-CS应用于此环境。为了获得更好的适应性,我们将D-CS与CS进行了比较。实验结果表明,D-CS在动态环境下具有良好的随机保持能力。引入本地解决方案比较策略和并发解决方案生成策略有助于获得具有随机性的动态环境的保留和查找功能。

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