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An indicator and adaptive region division based evolutionary algorithm for many-objective optimization
Applied Soft Computing ( IF 8.7 ) Pub Date : 2020-11-05 , DOI: 10.1016/j.asoc.2020.106872
Jiajun Zhou , Xifan Yao , Liang Gao , Chengyu Hu

Problems involving four or more objectives are termed Many-objective problems (MaOPs), which pose serious challenges to existing evolutionary algorithms (EAs). Although EAs via decomposition exhibit encouraging performance in handling MaOPs, they need a set of predefined weight vectors, which is not well adaptable to problems possessing various Pareto front (PF) shapes. Besides, the nature of subproblem formulations renders the overwhelming convergence property. In this paper, we introduce an indicator and adaptive region division based EA, referred to as IREA, which is free from the presetting of weight vectors. To be specific, an angular distance based space division module and a proximity-oriented indicator are incorporated into IREA, where the former highlights diversity adaptively via maximum angular distance while the latter emphasizes convergence in a local manner. Furthermore, the quality of mating pool is leveraged by a coordinate transformation assisted niche technique. The proposed IREA is compared with several prevalent many-objective EAs on scalable MaOPs with varying characteristics, as well as on the many-objective cloud manufacturing service composition problems. The experimental results demonstrate that IREA is highly competitive and can be used as an alternative for handling MaOPs.



中文翻译:

基于指标和自适应区域划分的多目标优化进化算法

涉及四个或更多目标的问题称为多目标问题(MaOP),这对现有的进化算法(EA)构成了严峻挑战。尽管通过分解的EA在处理MaOP方面表现出令人鼓舞的性能,但它们需要一组预定义的权重向量,这不适用于具有各种Pareto前沿(PF)形状的问题。此外,子问题公式的性质还具有压倒性的收敛性。在本文中,我们介绍了一种基于指标和自适应区域划分的EA,称为IREA,它无需权重向量的预设。具体而言,将基于角度距离的空间划分模块和面向距离的指示器并入IREA,前者通过最大角距离自适应地突出多样性,而后者则强调局部收敛。此外,交配池的质量通过坐标转换辅助的利基技术得到利用。在具有不同特性的可扩展MaOP上,以及在多目标云制造服务组合问题上,将提议的IREA与几种流行的多目标EA进行了比较。实验结果表明,IREA具有很强的竞争力,可以用作处理MaOP的替代方法。以及关于多目标云制造服务组合的问题。实验结果表明,IREA具有很强的竞争力,可以用作处理MaOP的替代方法。以及关于多目标云制造服务组合的问题。实验结果表明,IREA具有很强的竞争力,可以用作处理MaOP的替代方法。

更新日期:2020-11-06
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