| 混合蚁群优化算法应用研究 |
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| 引用本文： | 柴宝杰,刘大为. 混合蚁群优化算法应用研究[J]. 煤炭技术, 2009, 28(8) |
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| 作者姓名： | 柴宝杰 刘大为 |
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| 作者单位： | 1. 牡丹江师范学院,黑龙江,牡丹江,157012
2. 中国石油信息技术服务中心,北京,100872 |
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| 摘 要： | 结合粒子群算法的思想,提出用混合蚁群算法。其核心是应用粒子群算法对蚁群算法的3个控制参数(β,ρ,q0)进行优化,以及运用蚁群系统算法(ACS)寻找最短路径。新算法克服了参数选择对算法性能的影响,具体很强的全局搜索能力。新算法改进了传统蚁群算法的性能,取得了非常好的效果。
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| 关 键 词： | 蚁群算法 蚁群系统 粒子群算法 |
Research of Using a Hybrid Ant Colony Optimization Algorithm to Solve TSP |
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| CHAI Bao-jie,LIU Da-wei. Research of Using a Hybrid Ant Colony Optimization Algorithm to Solve TSP[J]. Coal Technology, 2009, 28(8) |
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| Authors: | CHAI Bao-jie LIU Da-wei |
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| Abstract: | The ant colony optimization (ACO) algorithm combining with the idea of the particle swarm optimization (PSO) algorithm is presented to solve the well known traveling salesman problem (TSP). Whose cores are that using PSO to optimize the comtrol parameters of ACO (β,ρ,q0) and applying ant colony system to routing. The new algorithm (ACSPSO) effectively overcomes the influence of comtrol paramelers of ACO and shows good global search capability. Simulation results show that ACSPSO improves the performance of ACO and the nice effects are obtained. |
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| Keywords: | ant colony algoithm ant colony system particle swarm algorithm traveling salesman problem |
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