| 蚁群与粒子群混合算法求解TSP问题 |
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| 引用本文： | 孙凯,吴红星,王浩,丁家栋. 蚁群与粒子群混合算法求解TSP问题[J]. 计算机工程与应用, 2012, 48(34): 60-63 |
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| 作者姓名： | 孙凯 吴红星 王浩 丁家栋 |
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| 作者单位： | 1.合肥工业大学 计算机与信息学院，合肥 2300092.安徽省徽商集团 信息中心，合肥 230061 |
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| 摘 要： | 旅行商问题（TSP）是最古老而且研究最广泛的组合优化问题。针对TSP问题，提出一种蚁群与粒子群混合算法（HAPA）。HAPA首先将蚁群划分成多个蚂蚁子群，然后把蚂蚁子群的参数作为粒子，通过粒子群算法来优化蚂蚁子群的参数，并在蚂蚁子群中引入了信息素交换操作。实验结果表明，HAPA在求解TSP问题中比传统算法和同类算法更具优越性。
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| 关 键 词： | 蚁群算法 粒子群优化算法 旅行商问题 |
Hybrid ant colony and particle swarm algorithm for solving TSP |
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| SUN Kai , WU Hongxing , WANG Hao , DING Jiadong. Hybrid ant colony and particle swarm algorithm for solving TSP[J]. Computer Engineering and Applications, 2012, 48(34): 60-63 |
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| Authors: | SUN Kai WU Hongxing WANG Hao DING Jiadong |
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| Affiliation: | 1.School of Computer and Information, Hefei University of Technology, Hefei 230009, China2.Information Center, Anhui Province Huishang Group, Hefei 230061, China |
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| Abstract: | The Traveling Salesman Problem （TSP） is the oldest and most extensively studied combinatorial optimization problem. For the traveling salesman problem, Hybrid Ant colony and Particle swarm Algorithm （HAPA） is proposed. The HAPA divides the ant colony into several ant sub colonies, then optimizes parameters of the ant sub colonies as particles by the particle swarm optimization algorithm, and introduces the operation of swapping the pheromone in each ant sub colony. Results show that the HAPA has more advantages than the traditional algorithm and the similar algorithm in solving the traveling salesman problem. |
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| Keywords: | Ant Colony Optimization Particle Swarm Optimization Traveling Salesman Problem |
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