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《Control and Decision》 2006-07
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An Improved Real-value Adaptive Genetic Algorithm

PAN Wei~(1,2),DIAO Hua-zong~1,JING Yuan-wei~2 (1.Department of Electric Detection,Shenyang Artillery College,Shenyang 110162,China;2.College of Information Science and Engineering,Northeastern University,Shenyang 110004,China.)  
The improvement problem of genetic algorithm is studied based on real coding.To the shortcomings that: the search is inefficient and it is easy to premature convergence,the parameter adjusting problem of genetic algorithm is discussed.The adaptive crossover probability and adaptive mutation probability are proposed,considering the influence of every generation to algorithm and the effect of different individual fitness in every generation.Three testing functions are used to validate the algorithm.The results thaw that the ultimate value,the average algebraic sum and the convergence probability all obtain the preferable values.
【Fund】: 国家自然科学基金项目(69974007);; 教育部高等学校博士学科点专项科研基金项目(20020145007)
【CateGory Index】: TP18
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