融合FDB策略和切线飞行的改进白鲸优化算法  

Improved BWO algorithm combining FDB strategy and tangent flight

作　　者：陈曦明 张军伟[1] Chen Ximing;Zhang Junwei(Beijing Institute of Space Launch Technology,Beijing 100076,China)

机构地区：[1]北京航天发射技术研究所,北京100076

出　　处：《计算机时代》2023年第11期46-51,共6页Computer Era

基　　金：国家自然科学基金项目(51605020)。

摘　　要：针对传统白鲸优化算法(BWO)存在的不足,提出一种融合适应度距离平衡(FDB)策略和切线飞行的改进白鲸优化算法。在种群初始化时引入基于莱维飞行扰动的Tent映射,增强了种群多样性;在BWO的探索和鲸落阶段融入FDB选择策略,跳出局部最优;利用切线飞行改进鲸落阶段的种群位置更新模式,提升收敛精确度。通过对8个常用的基准函数进行寻优试验,可证明相比于基本的BWO,所提改进算法具备更优越的鲁棒性和全局寻优能力。Considering the shortcomings of traditional BWO,an improved BWO algorithm combining FDB strategy and tangent flight is proposed.The Tent mapping based on Levy flight disturbance is introduced during the population initialization to enhance the population diversity,the FDB selection strategy is incorporated in the exploration and whale fall stages of BWO to jump out of the local optimum,and the tangent flight is used to improve the updating mode of population position in whale fall stage and improve the convergence accuracy.By performing optimization experiments on eight commonly used benchmark functions,it can be proved that the improved algorithm has better robustness and global optimization ability than the basic BWO.

关 键 词：白鲸优化算法 FDB策略 TENT映射 切线飞行 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]