基于hK1三角剖分的改进遗传算法

2008 International Seminar on Future Information Technology and Management Engineering Pub Date : 2008-11-20 DOI:10.1109/FITME.2008.158

Jingjun Zhang, Yanmin Shang, Ruizhen Gao, Yuzhen Dong

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引用次数: 0

摘要

提出了一种基于hK1三角剖分的改进遗传算法，用于双多模态函数的优化。该算法将最优问题转化为不动点问题的求解。最小点可以用Hessian矩阵来区分。多个典型函数的测试结果表明，该算法是有效的、高效的。

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An Improved Genetic Algorithm Based on hK1 Triangulation

An improved genetic algorithm based on the hK1 triangulation is proposed for optimization of dual multimodal function. With this algorithm, the optimal problems converse to solution of fixed point problems. The minimum points can be distinguished by using the Hessian Matrix. The test results of many typical functions indicated that the algorithm is valid and highly effective.

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2008 International Seminar on Future Information Technology and Management Engineering

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