| 基于优化成熟度的自适应蚁群优化算法 |
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| 引用本文： | 郭小芳.基于优化成熟度的自适应蚁群优化算法[J].西北师范大学学报,2010(6). |
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| 作者姓名： | 郭小芳 |
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| 作者单位： | 江苏科技大学计算机科学与工程学院; |
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| 基金项目： | 江苏省自然科学基金资助项目(BK2007708) |
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| 摘 要： | 通过深入分析蚁群算法中信息素更新系数对算法寻优能力与收敛速度的影响,定义了平均路径相似度(ATS)来表征寻优过程的成熟程度,据此自适应调整信息素更新系数,以提高算法收敛速度,并避免陷入局部最优.经过与典型蚁群算法在多个旅行商问题测试用例上进行比较,表明新算法具有更好的效果.
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| 关 键 词： | 蚁群优化 平均路径相似度 自适应参数控制 |
Adaptive ant colony optimization algorithm based on optimization maturity |
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| GUO Xiao-fang.Adaptive ant colony optimization algorithm based on optimization maturity[J].Journal of Northwest Normal University Natural Science (Bimonthly),2010(6). |
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| Authors: | GUO Xiao-fang |
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| Affiliation: | GUO Xiao-fang(School of Computer Science and Engineering,Jiangsu University of Science and Technology,Zhenjiang 212003,Jiangsu,China) |
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| Abstract: | By observing the effect of parameters on the performance of the ant colony system(ACS) algorithm in different optimization state,this paper presents a novel version of ACS based on the optimization maturity for obtaining self-adaptive parameters control.The adaptive ACS has been applied to optimize several benchmark TSP instances.The solution quality,convergence rate and global searching ability are favorably compared with the ACS.Experimental results confirm that our proposed method is effective and outper... |
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| Keywords: | ant colony optimization average tour similarity adaptive parameters control |
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