| 兼顾最优个体的模拟退火分层遗传算法 |
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| 引用本文： | 范朝冬,欧阳红林.兼顾最优个体的模拟退火分层遗传算法[J].萍乡高等专科学校学报,2013(3):57-61. |
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| 作者姓名： | 范朝冬 欧阳红林 |
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| 作者单位： | 湖南大学电气与信息工程学院 |
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| 基金项目： | 国家自然科学基金项目(61174140);博士点基金项目(20110161110035);湖南省科技计划重点项目(2010GK2022);长沙市科技计划重点项目(K1005018-11)的阶段性成果之一 |
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| 摘 要： | 针对传统分层遗传算法存在"发散"、收敛速度慢和最优解易丢失等缺陷,本文提出了一种改进的分层遗传算法,采用基于模拟退火思想的底层交叉和变异算子,避免底层算法的"发散"、提高收敛速度;设计了一种兼顾最优个体的高层选择算子,防止最优个体丢失。求解SAT问题的比较实验结果表明:求解成功率与收敛速度等算法性能均有较大提升。
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| 关 键 词： | 分层遗传算法 模拟退火 最优个体 SAT问题 |
Hierarchical Genetic Algorithm Based on Simulated Annealing and Optimal Individuals |
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| Institution: | Fan Chaodong;Ouyang Honglin;College of Electrical and Information Energy,Hunan University; |
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| Abstract: | To improve the defects of traditional hierarchical genetic algorithm,such as ＂divergence＂,slow convergence and easy loss of optimal solution,a promoted hierarchical genetic algorithm is proposed,which adopts bottom crossover and mutation operators based on simulated annealing to avoid ＂divergence＂ of underlying algorithm and improve convergence speed.The new high level selection operator which considers optimal individuals is designed to prevent loss of optimal individuals.Experimental results of solving the SAT problem show that the algorithm has some improvement in success rate and convergence speed etc. |
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| Keywords: | hierarchical genetic algorithm simulated annealing optimal individuals SAT problem |
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