引用本文:孙靖,巩敦卫.进化高维多目标优化研究进展[J].控制理论与应用,2018,35(7):928~938.[点击复制]
SUN Jing,GONG Dun-wei.Recent advances in evolutionary many-objective optimization[J].Control Theory and Technology,2018,35(7):928~938.[点击复制]
进化高维多目标优化研究进展
Recent advances in evolutionary many-objective optimization
摘要点击 3532  全文点击 2359  投稿时间:2018-01-22  修订日期:2018-06-28
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DOI编号  10.7641/CTA.2018.80067
  2018,35(7):928-938
中文关键词  高维多目标优化  进化优化  Pareto占优  目标缩减  偏好  集合进化
英文关键词  many-objective optimization  evolutionary optimization  pareto dominance  objective reduction  preference  set-based evolution  variation operator
基金项目  国家“973”计划项目(2014CB046306–2), 国家重点研发计划子课题(2018YFB1003802–01), 国家自然科学基金项目(61773384, 61703188, 6167 3404, 61763026)资助.
作者单位E-mail
孙靖 江苏省淮海工学院 sunj@hhit.edu.cn 
巩敦卫* 中国矿业大学 dwgong@vip.163.com 
中文摘要
      高维多目标优化问题是目标个数多于3的多目标优化问题. 尽管进化优化方法在多目标优化问题求解中显示了卓越的性能, 但是, 对于高维多目标优化问题, 已有方法存在目标维数难以扩展、Pareto占优关系无法区分进化个体, 以及多样性维护策略失效等困难. 因此, 高维多目标优化问题的高效求解引起进化优化界的高度关注. 本文将分别从新型占优关系、多样性维护策略、目标缩减、目标聚合、基于性能指标的选择、融入偏好、集合进化、变化算子、可视化技术, 以及应用等10个方面分类总结近年来进化高维多目标优化的研究成果, 通过分析已有研究存在的问题,指出今后可能的研究方向.
英文摘要
      Many-objective optimization problems are multi-objective ones with more than three objectives. Evolutionary optimization methods have outstanding performances on multi-objective optimization problems. State-of-the-art evolutionary multi-objective optimization methods, however, exist a plenty of severe shortcomings when solving many-objective optimization problems, such as the curse of the objective dimensionality, the incapability of the Pareto dominance in distinguishing evolutionary individuals, and the inefficacy of the diversity maintenance strategies. Therefore, how to efficiently tackle many-objective optimization problems have been attracting scholars in the evolutionary optimization community. In this paper, we will comprehensively review recent advances in evolutionary many-objective optimization from such aspects as novel dominance relations, diversity maintenance strategies, objective reduction, objective aggregation, indicator-based selection, preference integration, set-based evolution, variation operators, visualization technology as well as applications, and suggest several important topics to be further researched by analyzing the existing problems.