摘要
群智能算法是一种新兴的演化计算技术。常见的群智能理论研究算法有:粒子群算法、蚁群算法、蝙蝠算法等。蝙蝠算法模型简单、收敛速度快,虽具有强大的全局搜索性能,但其局部搜索相对简单,个体间缺乏信息互通,搜索能力差。针对这种缺陷,该文提供了一种基于质心策略的蝙蝠算法,首先对该算法进行了详细的公式化表述并对其执行流程做出了说明,然后将该算法与标准蝙蝠算法、粒子群优化算法进行了比较。仿真结果表明,改进的蝙蝠算法明显优于其他算法。
：Swarm intelligence algorithm is a new evolutionary computation technique.Common theoretical studies of swarm intelligence algorithm are ant colony algorithm , bat algorithm,and so on. Bat algorithm model is simple and although bat algorithm has a powerful search performance,something else about it is poor .To deal with the defect, in this paper, we put forward a new algorithm named bat algorithm based on barycenter strategy,which is formulated in detail and also compared with the standard bat algorithm and other optimization algorithms.Simulation results show that the improved algorithm is superior to other bat algorithms.
出处
《科技资讯》
2015年第35期239-240,242,共3页
Science & Technology Information
关键词
群体智能
蝙蝠算法
质心策略
Swarm Intelligence
Bat Algorithm
Barycenter Srategy
