约束多目标优化的MOEA/D:一些初步实验结果

2010 UK Workshop on Computational Intelligence (UKCI) Pub Date : 2010-11-09 DOI:10.1109/UKCI.2010.5625585

Muhammad Asif Jan, Qingfu Zhang

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引用次数: 82

摘要

本文对[1]中开发的MOEA/D-DE中的替换和更新方案进行了修改，以处理多目标优化问题中的约束。改进后的方案引入了一个惩罚函数来惩罚不可行的解。惩罚函数使用阈值来控制对不可行解的惩罚量。实验结果表明，这种惩罚方法是很有前途的。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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MOEA/D for constrained multiobjective optimization: Some preliminary experimental results

This paper modifies the replacement and update scheme in MOEA/D-DE developed in [1] for dealing with constraints in multiobjective optimization problems. The modified scheme introduces a penalty function to penalize infeasible solutions. The penalty function uses a threshold to control the amount of penalty to infeasible solutions. Experimental results have shown that this penalty method is very promising.

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2010 UK Workshop on Computational Intelligence (UKCI)

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