| 求解TSP问题的混合遗传微粒群算法 |
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| 引用本文： | 李剑,刘志明. 求解TSP问题的混合遗传微粒群算法[J]. 计算机与数字工程, 2009, 37(5): 33-34 |
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| 作者姓名： | 李剑 刘志明 |
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| 作者单位： | 湖北第二师范学院计算机科学与工程系,武汉,430060;湖北第二师范学院计算机科学与工程系,武汉,430060;技大学水电与数字化工程学院,武汉,430074 |
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| 摘 要： | 采用借鉴遗传算法的编码、交叉和变异操作的遗传微粒群算法对旅行商问题进行求解。针对微粒群算法的进化机制，设计了满足三条染色体交叉需要的分步式交叉算子。对多个基准测试实例的仿真计算表明，算法能有效的求解旅行商问题，在求解不同规模旅行商问题上性能均优于标准微粒群算法和离散二进制版本的微粒群算法。
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| 关 键 词： | 微粒群算法 旅行商问题 局部搜索 |
A Hybrid Genetic Particle Swarm Optimization for TSP |
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| Li Jian,Liu Zhiming. A Hybrid Genetic Particle Swarm Optimization for TSP[J]. Computer and Digital Engineering, 2009, 37(5): 33-34 |
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| Authors: | Li Jian Liu Zhiming |
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| Affiliation: | Department of Computer Science and Engineering;Hubei University of Education1;School of Hydropower & Information Engineering;Huazhong University of Science & Technology2 |
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| Abstract: | The genetic particle swarm optimization which is derived from particle swarm optimization(PSO) and incorporated with genetic coding,crossover and mutation operators was employed to solve traveling salesman problem(TSP).The algorithm was implemented for well-known benchmark cases,and the simulation results have shown the infeasibility and effectiveness of the algorithm,which outperformed the standard PSO and the discrete binary version of PSO in various benchmark cases. |
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| Keywords: | particle swarm optimization traveling salesman problem local search |
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