内蒙古民族大学学报（自然科学版）2025，Vol.40Issue(6)：51-62,12.DOI:10.14045/j.cnki.15-1220.2025.06.008
融合瞬态搜索与双向变异的改进白鲸优化算法及其应用
An Improved Beluga Whale Optimization Algorithm Integrating Transient Search and Bidirectional Mutation and Its Applications
摘要
Abstract
An improved Beluga Whale Optimization(BWO)algorithm,named Transient Search and Bidirec-tional Mutation-based Beluga Whale Optimization(TSBWO),is proposed to overcome the low convergence accu-racy,limited global search ability,and premature convergence of BWO.In the exploitation phase,a selective position update mechanism is introduced based on Transient Search Optimization(TSO).A stochastic decision factor guides whether to expand the search range via an oscillation term to enhance local search precision by combining the TSO transient coefficient with Lévy flight,achieving a balance between exploration and exploitation.Meanwhile,bidirec-tional mutation further improves search performance.The t-distribution mutation enhances global diversity,while dy-namic opposition-based learning perturbs current solutions to avoid local convergence.Experimental results show that compared with BWO and five other intelligent algorithms and four improved versions,TSBWO maintains high solution accuracy and convergence stability on eight different types of benchmark test functions.Its effectiveness and applicability are further validated on two engineering design problems.关键词
白鲸优化算法/瞬态搜索/t分布/动态反向学习/测试函数/工程设计Key words
Beluga Whale Optimization algorithm/transient search/t-Distribution/dynamic opposition-based learning/test functions/engineering design分类
信息技术与安全科学引用本文复制引用
张冰冰,姜静清,宋佳智,郭淑妮..融合瞬态搜索与双向变异的改进白鲸优化算法及其应用[J].内蒙古民族大学学报（自然科学版）,2025,40(6):51-62,12.基金项目
国家自然科学基金项目(62162050) （62162050）
内蒙古民族大学博士科研启动基金项目(KYQD23006) （KYQD23006）
