基于Pareto前沿和不动点理论的改进多目标遗传算法

2009 International Workshop on Intelligent Systems and Applications Pub Date : 2009-05-23 DOI:10.1109/IWISA.2009.5072719

Jingjun Zhang, Yanmin Shang, Ruizhen Gao, Yuzhen Dong

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引用次数: 1

摘要

针对多目标优化问题，提出了一种基于Pareto前沿和不动点理论的改进多目标遗传算法。该算法将不动点理论引入到多目标优化问题中，并对各子函数构造的权函数的解进行K1三角剖分，将最优问题转化为不动点问题。用排他法构造非支配集。实验结果表明，改进后的遗传算法收敛速度更快，能够得到分布范围更广的Pareto最优解。关键词:多目标优化;帕累托前沿;nondominated设置;遗传算法;不动点;K1三角

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An Improved Multi-Objective Genetic Algorithm Based On Pareto Front and Fixed Point Theory

For multi-objective optimization problems, an improved multi-objective genetic algorithm based on Pareto Front and Fixed Point Theory is proposed in this paper. In this Algorithm, the fixed point theory is introduced to multi-objective optimization questions and K1 triangulation is carried on to solutions for the weighting function constructed by all subfunctions, so the optimal problems are transferred to fixed point problems. The non-dominated-set is constructed by the method of exclusion. The experimental results show that this improved genetic algorithm convergent faster and is able to achieve a broader distribution of the Pareto optimal solution. Keywords— multi-objective optimization; Pareto Front; nondominated set; genetic algorithm; fixed point; K1 triangulation

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2009 International Workshop on Intelligent Systems and Applications

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