【24h】

Application of Improved Ant Colony Algorithm

机译:改进蚁群算法的应用

获取原文

摘要

A stochastic optimization algorithm is proposed by combining ant colony (ACO) algorithm with Artificial Fish-Swarm Algorithm (AFSA) for solving continuous space optimization problems. The algorithm is improved with the rapid search capability of AFSA and the good search characteristics of ACO, and the convergence speed of the presented algorithm is also improved for avoiding being trapped in local optimization. The improved algorithm has been tested for varieties of functions. And the algorithm can handle these optimization problems very wel1.
机译:将蚁群算法与人工鱼群算法相结合,提出了一种随机优化算法,用于求解连续空间优化问题。通过AFSA的快速搜索能力和ACO的良好搜索特性对算法进行了改进,并且所提算法的收敛速度也得到了提高,避免了陷入局部优化中。改进的算法已针对各种功能进行了测试。该算法可以很好地处理这些优化问题。

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