| 基于改进自适应遗传算法的仿真研究 |
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| 引用本文： | 姜静,谭博学,姜琳.基于改进自适应遗传算法的仿真研究[J].山东理工大学学报,2008,22(6). |
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| 作者姓名： | 姜静 谭博学 姜琳 |
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| 作者单位： | 山东理工大学电气与电子工程学院 河南安阳钢铁公司第二炼钢厂 |
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| 摘 要： | 交叉概率Pc和变异概率Pm是遗传算法中重要的参数,自适应遗传算法中Pc和Pm能根据个体适应度差异自适应地调节其大小,在快速收敛和全局最优之间获得了较好的平衡,但自适应遗传算法对于进化初期不利.改进的自适应遗传算法避免了进化初期较优个体处于停滞不前的状态.分别用3种算法对典型的测试函数进行训练,仿真结果表明:改进的自适应遗传算法在收敛速度和寻最优解方面是最优的.
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| 关 键 词： | 自适应 遗传算法 参数选择 |
Simulation analysis based on improved self-adaptive genetic algorithm |
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| JIANG Jing,TAN Bo-xue,JIANG Lin.Simulation analysis based on improved self-adaptive genetic algorithm[J].Journal of Shandong University of Technology:Science and Technology,2008,22(6). |
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| Authors: | JIANG Jing TAN Bo-xue JIANG Lin |
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| Abstract: | Crossover and mutation probabilities are important parameters in genetic algorithm,self-adaptive genetic algorithm can reach good balance between convergence speed and global optimization,but it is not suitable to use the algorithm at the beginning of the evolution.The improved algorithm can avoid this shortcoming.Training the typical test function by genetic algorithm,self-adaptive genetic algorithm and the improved algorithm,the improved algorithm outperforms the other two ones. |
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| Keywords: | self-adaptive genetic algorithm parameter selection |
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