| 应用遗传算法原理确定函数的最优解 |
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| 引用本文： | 乔均俭,付君丽,徐雅玲.应用遗传算法原理确定函数的最优解[J].微计算机信息,2007,23(18):240-241,192. |
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| 作者姓名： | 乔均俭 付君丽 徐雅玲 |
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| 作者单位： | 1. 071000,河北保定,河北农业大学理学院
2. 071000,河北保定,河北农业大学海洋学院 |
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| 摘 要： | 本文主要介绍了一种新型的、随机性的全局优化方法即遗传算法.一般应用于在一个问题的解集中查找最优解情况,如是一个问题有多个答案,但是想查找一个最优答案的话,那么使用遗传算法可以达到更快更好的效果.即在浮点编码遗传算法中加入一个函数,构成适于不可微函数全局优化的遗传算法.该算法改善了遗传算法的局部搜索能力,显著提高了遗传算法求得全局解的概率.
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| 关 键 词： | 遗传算法 函数极值 全局最优 |
| 文章编号： | 1008-0570（2007）06-3-0240-02 |
| 修稿时间： | 2007-05-032007-06-05 |
Using Genetic Algorithms Gaint Best Answer of Functions |
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| QIAO JUNJIAN,FU JUNLI,XU YALING.Using Genetic Algorithms Gaint Best Answer of Functions[J].Control & Automation,2007,23(18):240-241,192. |
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| Authors: | QIAO JUNJIAN FU JUNLI XU YALING |
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| Affiliation: | QIAO JUNJIAN FU JUNLI XU YALING |
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| Abstract: | A hybrid computational intellective algorithm for locating the global optima of in differentiable nonlinear function was put forward by setting the Powell algorithm in real-code genetic algorithm. The hybrid approach improved the local searching ability of the genetic algorithm and promoted the probability for the global optima greatly. Because only the objective values are used, the hy- brid approach is a generalized genetic algorithm for global optima of differentiable and indifferentiable nonlinear functions. |
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| Keywords: | genetic algorithms the function pole value global optima |
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