多目标优化
选择(遗传算法)
领域(数学)
多样性(控制论)
进化算法
数学优化
计算机科学
进化计算
数学
机器学习
人工智能
纯数学
作者
Ke Shang,Hisao Ishibuchi,Linjun He,Lie Meng Pang
标识
DOI:10.1109/tevc.2020.3013290
摘要
Hypervolume is widely used as a performance indicator in the field of evolutionary multiobjective optimization (EMO). It is used not only for performance evaluation of EMO algorithms (EMOAs) but also in indicator-based EMOAs to guide the search. Since its initial proposal in the late 1990s, a wide variety of studies have been done on various topics, including hypervolume calculation, optimal μ-distribution, subset selection, hypervolume-based EMOAs, and extensions of the hypervolume indicator. However, currently there is no work to systematically survey the hypervolume indicator for these topics whereas it has been frequently used in the EMO field. This article aims to fill this gap and provide a comprehensive survey on the hypervolume indicator. We expect that this survey will help EMO researchers to understand the hypervolume indicator more deeply and thoroughly, and promote further utilization of the hypervolume indicator in the EMO field.
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