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首页> 外文会议>International Symposium on Computational and Information Science(CIS 2004); 20041216-18; Shanghai(CN) >The Geometric Constraint Solving Based on Mutative Scale Chaos Genetic Algorithm
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The Geometric Constraint Solving Based on Mutative Scale Chaos Genetic Algorithm

机译：基于变尺度混沌遗传算法的几何约束求解

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摘要

The constraint problem can be transformed to an optimization problem. In this paper a new hybrid algorithm-MSCGA was introduced which mixes genetic algorithm with chaos optimization method. The character of this new method is that the mechanism of the GA was not changed but the search space and the coefficient of adjustment was reduced continually and this can lead generation to evolve to the next generation in order to produce better optimization individuals. It can improve the performance of the GA and get over the disadvantage of the GA. The examination indicates that this algorithm can show a better performance than the normal GA and other hybrid methods in solving a geometric constraint and acquires a satisfying result.
机译：约束问题可以转化为优化问题。本文提出了一种新的混合算法-MSCGA，它将遗传算法与混沌优化方法相结合。这种新方法的特点是，遗传算法的机制没有改变，但是搜索空间和调整系数不断减小，这可以导致一代进化到下一代，从而产生更好的优化个体。它可以提高GA的性能并克服GA的缺点。检验表明，该算法在解决几何约束方面比普通遗传算法和其他混合方法表现出更好的性能，取得了令人满意的结果。

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