华中科技大学学报（自然科学版）2026，Vol.54Issue(5)：46-53,8.DOI:10.13245/j.hust.240810
基于双变异繁殖和HAD的多模态多目标差分算法
Multimodal multi-objective differential evolution algorithm based on double mutation reproduction and HAD strategy
摘要
Abstract
To improve the balance of algorithm performance in decision space and objective space,a multimodal multi-objective differential evolution algorithm based on double mutation reproduction and heterogeneity archive diversity(HAD)strategy(MMODE_DM_HAD)was proposed.The double mutation reproduction strategy was able to provide different mutation strategies for individuals of different grades to achieve a balance of population diversity and convergence.The HAD strategy archived the individuals separately according to their different properties and selected appropriate candidate solutions based on diversity criteria to achieve the maintenance of population diversity and improve the quality of solutions.Compared with 7 multimodal multi-objective optimization algorithms,MMODE_DM_HAD was validated on 14 test problems.Experimental results show that MMODE_DM_HAD ranks first in rHV values on all test problems,and it achieves the optimal IGDx values on 5 test problems and the suboptimal IGDx values on 5 test problems.While ensuring the performance of the objective space,MMODE_DM_HAD can fully explore the decision space and overall outperform the other comparative algorithms.关键词
多模态多目标优化/差分进化算法/双变异繁殖策略/HAD策略/多目标优化Key words
multimodal multi-objective optimization/differential evolution/double mutation reproduction strategy/HAD strategy/multi-objective optimization分类
信息技术与安全科学引用本文复制引用
王珊珊,向思颖,王嘉诚,曾亮..基于双变异繁殖和HAD的多模态多目标差分算法[J].华中科技大学学报（自然科学版）,2026,54(5):46-53,8.基金项目
湖北省重点研发计划资助项目(2023BAB094) （2023BAB094）
湖北省教育厅科学研究计划重点资助项目(D20211402) （D20211402）
太阳能高效利用及储能运行控制湖北省重点实验室2023年度开放研究基金资助项目(HBSEES202309). （HBSEES202309）
