| 交叉变异的连续蚁群优化算法 |
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| 引用本文： | 张火明,高明正,张晓菲.交叉变异的连续蚁群优化算法[J].中国计量学院学报,2009,20(3):259-262,273. |
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| 作者姓名： | 张火明 高明正 张晓菲 |
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| 作者单位： | 中国计量学院,计量测试工程学院,浙江,杭州,310018 |
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| 基金项目： | 国家自然科学青年基金资助项目 |
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| 摘 要： | 研究了应用于连续空间优化问题的蚁群算法,给出了信息素的留存方式以及搜索策略.另外,针对蚁群算法易陷入局部最优的缺点,在最优蚂蚁周围进行了精细搜索,并加入了自适应的交叉变异算子,从而改进了蚁群算法的全局优化性能.数值仿真结果表明,该算法是一种有效的优化算法.
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| 关 键 词： | 蚁群算法 优化算法 交叉算子 变异算子 |
Continuous ant colony optimization algorithm based on crossover and mutation |
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| ZHANG Huo-ming,GAO Ming-zheng,ZHANG Xiao-fei.Continuous ant colony optimization algorithm based on crossover and mutation[J].Journal of China Jiliang University,2009,20(3):259-262,273. |
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| Authors: | ZHANG Huo-ming GAO Ming-zheng ZHANG Xiao-fei |
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| Affiliation: | (College of Metrology and Measurement Engineering, China Jiliang University, Hangzhou 310018, China) |
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| Abstract: | The ant colony optimization （ACO） algorithm for solving optimization problems in continuous space investigated. Both the remaining way of pheromone and the searching strategy are presented. Moreover, the shortcoming it that ACO easily trapped into local optimum improved by carrying out fine searching near the best ant and by adding the crossover and mutation operator so that the global optimization performance of ACO enhanced. The numerical simulation results demonstrate that the proposed algorithm is effective. |
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| Keywords: | ACO optimization algorithm crossover operator mutation operator |
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