| 改进的自适应遗传算法在函数优化中的应用* |
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| 引用本文： | 杨从锐,钱 谦,王锋,孙铭会.改进的自适应遗传算法在函数优化中的应用*[J].计算机应用研究,2018,35(4). |
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| 作者姓名： | 杨从锐 钱 谦 王锋 孙铭会 |
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| 作者单位： | 昆明理工大学云南省计算机技术应用重点实验室,昆明理工大学云南省计算机技术应用重点实验室,昆明理工大学云南省计算机技术应用重点实验室,吉林大学计算机科学与技术学院 |
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| 基金项目： | 国家自然科学基金(31300938，61462053，61300145)；吉林大学符号计算与知识工程教育部重点实验室开放课题资助(93K172016K10) |
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| 摘 要： | 针对传统遗传算法在复杂函数优化的寻优搜索中容易陷入局部极值,搜索效率低,不稳定等特点,提出一种改进的自适应遗传算法,该算法的思想是根据进化中种群适应度的集中分散的程度非线性地自适应调节遗传进化的运算流程和交叉概率Pc、变异概率Pm的值,从而能更好地产生新的个体摆脱局部极值搜索到全局最优解,并采取最优保存策略来保证改进的自适应遗传算法的收敛性。仿真实验结果表明,与现存其他算法相比,改进的自适应遗传算法在全局寻优的收敛速度、最优解、求解精度、和稳定性等方面都有了较大的改进和提高。
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| 关 键 词： | 自适应遗传算法 函数优化 求解精度 种群适应度 |
| 收稿时间： | 2016/12/19 0:00:00 |
| 修稿时间： | 2018/2/27 0:00:00 |
The Application of an Improved Adaptive Genetic Algorithm in Function Optimization |
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| YANG Cong-rui,QIAN Qian,Wang Feng and SUN Ming-hui.The Application of an Improved Adaptive Genetic Algorithm in Function Optimization[J].Application Research of Computers,2018,35(4). |
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| Authors: | YANG Cong-rui QIAN Qian Wang Feng and SUN Ming-hui |
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| Affiliation: | Yunnan Key Laboratory of Computer Technology Applications,Kunming University of Science and Technology,,, |
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| Abstract: | Adaptive genetic algorithm has been proposed to improve the performance of function optimization. However, there are some disadvantages for traditional adaptive genetic algorithm, such as low efficiency and instability. This study improved the adaptive genetic algorithm by adaptively altering the process of genetic algorithm, dynamically changing the Pc and Pm values, and using an elitist strategy. Two complex function optimization problems were used for simulation. The result shows that the improved adaptive genetic algorithm has a great improvement in many aspects of the global optimization, such as the convergence rate, the optimal solution, and the stability. |
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| Keywords: | adaptive genetic algorithm function optimization solution precision fitness values of the populations |
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