郜振华,吴昊.一种改进的混合蝙蝠算法[J].南华大学学报(自然科学版),2019,33(1):62~66.[GAO Zhenhua,WU Hao.An Improved Hybrid Bat Algorithm[J].Journal of University of South China(Science and Technology),2019,33(1):62~66.]
一种改进的混合蝙蝠算法
An Improved Hybrid Bat Algorithm
投稿时间:2018-11-21  
DOI:
中文关键词:  蝙蝠算法  混合算法  分组迭代
英文关键词:bat algorithm  hybrid algorithm  group iteration
基金项目:
作者单位E-mail
郜振华 安徽工业大学 管理科学与工程学院,安徽 马鞍山 243000 1013823212@qq.com 
吴昊 安徽工业大学 管理科学与工程学院,安徽 马鞍山 243000  
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中文摘要:
      为解决基本蝙蝠算法中存在的易陷入局部最优且求解精度不足的问题,提出一种改进的混合蝙蝠算法,引入了分组迭代模式和多种速度迭代公式加强了全局搜索能力,更新了种群领域搜索公式的基础上引用了t分布作为种群最优解的领域搜索方式,补足了蝙蝠算法的局部搜索能力,避免了算法陷入局部最优解。通过多个标准测试函数的实验验证改进的混合蝙蝠算法能有效解决基本蝙蝠算法中出现的问题。
英文摘要:
      In order to solve the problem that the basic bat algorithm is easy to fall into the local optimal and the precision of solving is insufficient,an improved hybrid bat algorithm is proposed,the packet iteration mode and various velocity iteration formulas are introduced to strengthen the global search ability,and the domain search method of t distribution as the optimal solution of the population is referenced on the basis,the local search ability of BAT algorithm is supplemented to avoid the algorithm falling into the local optimal solution.Through the experiment of several standard test functions,it is proved that the improved hybrid bat algorithm can effectively solve the problems in the basic bat algorithm.
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