基于存档的多目标鱼鹰优化算法  

Multi-Objective Osprey Optimization Algorithm Based on Archive

作　　者：李奕轩 田云娜[1] LI Yi-xuan;TIAN Yun-na(School of Mathematics and Computer Science,Yan'an University,Yan'an 716000,China)

机构地区：[1]延安大学数学与计算机科学学院,陕西延安716000

出　　处：《数学的实践与认识》2025年第1期158-171,共14页Mathematics in Practice and Theory

基　　金：国家自然科学基金(61763046,62041212);延安大学研究生专项研究项目(YCX20222071);国家大学生创新创业训练计划项目(202110719031)。

摘　　要：针对鱼鹰优化算法无法求解多目标优化问题,提出一种多目标鱼鹰优化算法.首先引入存档机制存储非支配解,促进算法的收敛;然后使用顶级鱼鹰个体选择机制从存档中选择最优鱼鹰个体;最后使用自适应差分t分布变异增强算法的全局搜索能力.将所提算法与其他5种算法在CEC2020多模态多目标测试集中15个函数上进行测试,实验结果表明,所提算法得到的帕累托最优解集具有良好的多样性和收敛性.此外,通过焊接梁设计问题的实验对比分析,验证了所提算法在实际应用中的有效性和实用性.Aiming at the problem that the osprey optimization algorithm cannot solve the multi-objective optimization problem,a multi-objective osprey optimization algorithm is proposed.Firstly,the archiving mechanism is introduced to store non-dominated solutions and promote the convergence of the algorithm.Then use the top osprey individual selection mechanism to select the optimal osprey individual from the archive;finally,the adaptive differential t distribution mutation is used to enhance the global search ability of the algorithm.The proposed algorithm and other five algorithms are tested on 15 functions in CEC2020multi-modal multi-objective test set.The experimental results show that the Pareto optimal solution set obtained by the proposed algorithm has good diversity and convergence,and can effectively solve the multi-objective optimization problem.In addition,the effectiveness and practicability of the proposed algorithm in practical application are verified by the experimental comparison and analysis of the design problem of welded beam.

关 键 词：鱼鹰优化算法 存档机制 拥挤度 差分t分布变异 焊接梁设计问题 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]