| 基于遗传算法的混合蚁群算法 |
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| 引用本文： | 肖宏峰,谭冠政.基于遗传算法的混合蚁群算法[J].计算机工程与应用,2008,44(16):42-45. |
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| 作者姓名： | 肖宏峰 谭冠政 |
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| 作者单位： | 1. 湖南师范大学,计算机教学部,长沙,410081;中南大学,信息科学与工程学院,机器人研究所,长沙,410083
2. 中南大学,信息科学与工程学院,机器人研究所,长沙,410083 |
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| 基金项目： | 国家自然科学基金
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教育部高等学校博士学科点专项科研基金 |
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| 摘 要： | 提出了一种新的求连续空间最优值的蚁群算法。结合遗传算法和蚁群算法各自的优点以及两种算法融合基础,提出了遗传算法融入到蚁群算法融合中的两种新策略,第一种策略是先利用遗传算法具有比较强的全局搜索能力,在大范围内寻找一组解,然后以此为基础,用蚁群算法快速寻找最优解X*best;另一种策略是利用遗传算法交叉操作产生蚁群算法中的新旅行路径,以此提高蚁群算法的全局搜索能力。用上述策略构造两个基于遗传算法的混合遗传算法。用测试函数Rosenbrock和测试函数Shubert验证了混合蚁群算法的正确性。
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| 关 键 词： | 遗传算法 混合蚁群算法 算法融合 连续空间优化 |
| 文章编号： | 1002-8331(2008)16-0042-04 |
| 收稿时间： | 2007-7-20 |
| 修稿时间： | 2007年7月20日 |
Hybrid Ant Colony Algorithm based on Genetic Algorithm |
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| XIAO Hong-feng,TAN Guan-zhen.Hybrid Ant Colony Algorithm based on Genetic Algorithm[J].Computer Engineering and Applications,2008,44(16):42-45. |
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| Authors: | XIAO Hong-feng TAN Guan-zhen |
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| Affiliation: | 1.Department of Computer Teaching，Hunan Normal University，Changsha 410081，China 2.Robotic Institution，College of Information Science &; Engineering，Central South University，Changsha 410083，China |
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| Abstract: | Propose a new Ant Colony System(ACS) for obtaining optimal value of continuous space.Comparing their advantages and disadvantages between Genetic Algorithm(GA) and Ant Colony System and analyzing their basic fusion condition,propose two new strategies of fusing GA into ACS:One is first using genetic algorithm to obtain some rough solutions to the problem and then obtaining the more precise solutions X*best by ACS,the other is improving the ability of global search by using two tour paths in ACS to generate another two new tour paths like crossover operation of GA.Based on above new ideas,two new hybrid ant colony systems based on GA respectively called GA-HACS-I and GA-HACS-II are built in this paper.At last,verify the correction of GA-HACS-I and GA-HACS-II by test function Rosenbrock and test function Shubert. |
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| Keywords: | genetic algorithm hybrid ant colony system algorithm fusion optimization of continuous space |
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