首页> 外文会议>International conference on swarm, evolutionary, and memetic computing >Neighborhood Search Based Artificial Bee Colony Algorithm for Numerical Function Optimization
【24h】

Neighborhood Search Based Artificial Bee Colony Algorithm for Numerical Function Optimization

机译:基于邻域搜索的人工蜂群算法优化数值函数

获取原文
获取外文期刊封面目录资料

摘要

In this paper we investigate about the Neighborhood search mechanisms to improve the performance of Artificial Bee Colony (ABC) on shifted and rotated benchmark functions, proposed in CEC 2005. Although basic version of ABC has been provided with adaptive search mechanism, it will not be able to tackle complex functions with much accuracy unless it was enriched with an efficient neighborhood search scheme. Experimental results have explicitly shown that Neighborhood search based ABC (NS-ABC) performed superiorly well over other variants of ABC.
机译:在本文中,我们研究了在CEC 2005中提出的邻域搜索机制,以提高人工蜂群(ABC)在移动和旋转基准功能上的性能。尽管ABC的基本版本已提供了自适应搜索机制,但它不会除非使用有效的邻域搜索方案进行了扩充,否则它能够以很高的精度处理复杂的功能。实验结果明确表明,基于邻域搜索的ABC(NS-ABC)的性能优于ABC的其他变体。

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