多模态多目标优化综述  

A survey on multimodal multiobjective optimization

作　　者：岳彩通 梁静[1] 瞿博阳[2] 于坤杰 王艳丽[1] 胡毅 YUE Cai-tong;LIANG Jing;QU Bo-yang;YU Kun-jie;WANG Yan-li;HU Yi(School of Electrical Engineering,Zhengzhou University,Zhengzhou 450001,China;School of Electric&Information Engineering,Zhongyuan University of Technology,Zhengzhou 450007,China)

机构地区：[1]郑州大学电气工程学院,郑州450001 [2]中原工学院电子信息学院,郑州450007

出　　处：《控制与决策》2021年第11期2577-2588,共12页Control and Decision

基　　金：国家自然科学基金项目(61922072,61976237,61876169,61673404,61806179).

摘　　要：随着工业生产和日常生活需求的多样化,单个解决方案已经无法满足生产生活的需求.多模态优化可以为决策者提供多个可行方案,但是早期对多模态优化的研究局限在单目标优化中.在多目标优化中也存在多模态优化问题,其存在多个全局或局部帕累托最优解集,找到这些最优解集具有重大的理论和实际意义.鉴于此,首先,介绍多模态多目标优化问题的特点和求解难点;其次,综述求解此类问题的主要方法,总结这些方法的优缺点;再次,介绍常用的多模态多目标优化标准测试函数集和性能评价指标;最后,给出多模态多目标优化的应用领域及未来的研究方向.As the requirements in our daily lives and industrial production become diverse,a single solution cannot meet their demands anymore.Multimodal optimization can provide multiple feasible solutions.However,most of the previous researches on multimodal optimization focus on single-objective optimization.In fact,there are multimodal problems in multiobjective optimization,which,have multiple local or global Pareto sets and it is of great theoretical and practical significance to find these Pareto sets.Therefore,first,this paper introduces the features and challenges of multimodal multiobjective problems.Second,a survey on existing multimodal multiobjective optimization algorithms is given.Third,multimodal multiobjective benchmark problems and performance indicators are introduced.Finally,the applications and future research works are given.

关 键 词：多模态多目标优化 多模态优化 测试函数 全局优化 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]