华东理工大学学报（自然科学版）2017，Vol.43Issue(4)：525-532,562,9.DOI:10.14135/j.cnki.1006-3080.2017.04.011
一种基于椋鸟群行为的改进型蝙蝠算法
An Improved Bat Algorithm Based on Starling Flock Behavior
胡飞 1孙自强1
作者信息
- 1. 华东理工大学化工过程先进控制和优化技术教育部重点实验室,上海 200237
- 折叠
摘要
Abstract
Bat algorithm (BA) is a new metaheuristic algorithm.However,the standard BA has some shortcomings,e.g.,low convergence precision and easily relapsing into the local optima.In this work,by introducing the collective behavior of the starling group into BA algorithm,the searching range of the standard BA algorithm can be effectively improved.Besides,a linear decreasing weight is introduced to balance the global search and the local search.Simulation results from Benchmark functions show that the improved algorithm can effectively avoid the local optimum and attain higher convergence precision.关键词
蝙蝠算法(BA)/椋鸟群行为/权重/局部最优Key words
bat algorithm (BA)/starling group behavior/weight/local optima分类
信息技术与安全科学引用本文复制引用
胡飞,孙自强..一种基于椋鸟群行为的改进型蝙蝠算法[J].华东理工大学学报（自然科学版）,2017,43(4):525-532,562,9.
