基于IGD^+S指标的高维多目标进化算法  

Multi-objective Evolutionary Algorithm Based on IGD^+S

作　　者：黎明[1,2] 段茹茹 陈昊[1,2] 谢惠华 LI Ming;DUAN Ruru;CHEN Hao;XIE Huihua(School of Information Engineering,Nanchang Hangkong University,Nanchang 330063;Key Laboratory of Nondestructive Testing,Ministry of Education,Nanchang Hangkong University,Nanchang 330063)

机构地区：[1]南昌航空大学信息工程学院,南昌330063 [2]南昌航空大学无损检测技术教育部重点实验室,南昌330063

出　　处：《模式识别与人工智能》2019年第9期800-810,共11页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金项目(No.61866025,61772255,61440049);江西省图像处理与模式识别重点实验室开放基金项目(No.ET201604246);江西省研究生创新专项资金项目(No.YC2017-S327);江西省优势科技创新团队计划项目(No.20152BCB24004)资助~~

摘　　要：如何有效评价个体是处理高维多目标优化问题的关键.文中提出改进的反世代距离(IGD+S)指标,以反世代距离(IGD)指标为原型,融合修改的反世代距离(IGD+)指标的弱支配性,增加无贡献个体概念,可综合评价解集收敛性和多样性.将IGD+S指标嵌入进化算法框架中,提出基于IGD+S指标的高维多目标进化算法.在环境选择过程中,根据IGD+S选择优良个体.实验表明,文中算法在处理DTLZ问题和WFG问题上具有良好的竞争力.How to evaluate solutions effectively is a key to solving many-objective optimization problem.An inverted generation distance(IGD + S) indicator is proposed based on IGD indicator, incorporating weak dominance of IGD + indicator and employing the concept of non-contributing individuals.Convergence and diversity of solution set are evaluated comprehensively.IGD + S indicator is embedded in the framework of evolutionary algorithms, and a multi-objective evolutionary algorithm based on IGD + S indicator is presented.In the process of environmental selection, excellent solutions are selected according to enhanced IGD + S indicator.Experimental results demonstrate that the proposed algorithm is competitive in DTLZ problems and WFG problems.

关 键 词：高维多目标优化 环境选择 进化算法 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]