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| 基于局部优化策略求解TSP的蚁群算法* | |
| 引用本文： | 龚本灿,李腊元,蒋廷耀,汪祥莉.基于局部优化策略求解TSP的蚁群算法*[J].计算机应用研究,2008,25(7):1974-1976. |
| 作者姓名： | 龚本灿 李腊元 蒋廷耀 汪祥莉 |
| 作者单位： | 1. 三峡大学,电气信息学院,湖北,宜昌,443002;武汉理工大学,计算机学院,武汉,430063 2. 武汉理工大学,计算机学院,武汉,430063 3. 三峡大学,电气信息学院,湖北,宜昌,443002 |
| 基金项目： | 国家自然科学基金资助项目(60672137);教育部博士点基金资助项目（20060497015） |
| 摘 要： | 为了克服基本蚁群算法收敛速度慢、易于停滞的缺陷，提出了一种基于局部优化策略的蚁群算法（LOACA）。该算法根据TSP的特点,采用了三种局部优化算子来交换搜索路径中城市的位置,以改进解的质量。以TSP为例进行的实验结果表明，该算法优于ACA和ACAGA。 |
| 关 键 词： | 蚁群算法 局部优化 旅行商问题 |
Ant colony algorithm based on local optimization for TSP |
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| GONG Ben-can,LI La-yuan,JIANG Ting-yao,WANG Xiang-li.Ant colony algorithm based on local optimization for TSP[J].Application Research of Computers,2008,25(7):1974-1976. | |
| Authors: | GONG Ben-can LI La-yuan JIANG Ting-yao WANG Xiang-li |
| Affiliation: | (1.College of Electrical Engineering & Information Technology, China Three Gorges University, Yichang Hubei 443002, China;2.College of Computer Science & Technology, Wuhan University of Technology, Wuhan 430063, China) |
| Abstract: | This paper proposed an ant colony algorithm based on local optimization (LOACA) to avoid the default of slow convergence speed and early stagnation in the basic ant colony algorithm (ACA). According to the features of TSP, it used three local optimization operations to exchange the position of cities in the search paths to gain the better solutions. Experimental results for solving TSP show that the proposed algorithm performs better than ACA and ACAGA. |
| Keywords: | ant colony algorithm local optimization TSP (traveling salesman problem) |
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