摘要
为了改善基本蝙蝠算法(bat-inspired algorithm,BA)的求解性能,提高其搜索效率,避免其搜索过程陷入局部最优,利用Fuch映射对基本蝙蝠算法的局部最优解的邻域和蝙蝠的频率变化区间进行混沌遍历搜索,提出了一种新型混合蝙蝠算法——Fuch混沌蝙蝠算法(FCBA).仿真计算结果表明:与BA相比,FCBA具有较好的收敛性能,能够较快地收敛于测试算例的全局最优解.
In order to improve the solving performance of the original bat-inspired algorithm （BA）, increase its searching efficiency, and avoid falling into local optimal solution, the neighborhood of the local optimum and the frequency interval in the original BA were optimized by using the chaos optimization method based on Fuch mapping. Furthermore, a new hybrid bat- inspired algorithm named as Fuch chaos bat-inspired algorithm （FCBA） was proposed. The numerical results show that FCBA has better convergence performance,and can converge faster to the optimal solution of numerical examples.
出处
《上海理工大学学报》
CAS
北大核心
2014年第1期26-30,共5页
Journal of University of Shanghai For Science and Technology
基金
上海市大学生创新训练基金资助项目(201210252057)
上海市高校青年教师培养计划资助项目(slg12010)
高等学校博士学科点专项科研基金联合资助项目(20123120120005)
上海市教委科研创新资助项目(14YZ090)
上海理工大学国家级培育课题资助项目(13XGQ07)
关键词
蝙蝠算法
Fuch映射
混沌优化
bat-inspired algorithm
Fuch mapping
chaos optimization
