A combined constraint handling framework: an empirical study

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• 作者：Chengyong Si ; Junjie Hu ; Tian Lan ; Lei Wang ; Qidi Wu
• 关键词：Constrained optimization ; Constraint handling techniques ; Combined constraint handling framework (CCHF) ; Differential evolution ; Ranking methods
• 刊名：Memetic Computing
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：9
• 期：1
• 页码：69-88
• 全文大小：
• 刊物类别：Engineering
• 刊物主题：Appl.Mathematics/Computational Methods of Engineering; Artificial Intelligence (incl. Robotics); Complex Systems; Control, Robotics, Mechatronics; Bioinformatics; Applications of Mathematics;
• 出版者：Springer Berlin Heidelberg
• ISSN：1865-9292
• 卷排序：9

文摘

This paper presents a new combined constraint handling framework (CCHF) for solving constrained optimization problems (COPs). The framework combines promising aspects of different constraint handling techniques (CHTs) in different situations with consideration of problem characteristics. In order to realize the framework, the features of two popular used CHTs (i.e., Deb’s feasibility-based rule and multi-objective optimization technique) are firstly studied based on their relationship with penalty function method. And then, a general relationship between problem characteristics and CHTs in different situations (i.e., infeasible situation, semi-feasible situation, and feasible situation) is empirically obtained. Finally, CCHF is proposed based on the corresponding relationship. Also, for the first time, this paper demonstrates that multi-objective optimization technique essentially can be expressed in the form of penalty function method. As CCHF combines promising aspects of different CHTs, it shows good performance on the 22 well-known benchmark test functions. In general, it is comparable to the other four differential evolution-based approaches and five dynamic or ensemble state-of-the-art approaches for constrained optimization.