| 一种新改进的粒子群优化算法 |
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| 引用本文： | 时贵英,吴雅娟,倪红梅.一种新改进的粒子群优化算法[J].长春光学精密机械学院学报,2011(2):135-137. |
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| 作者姓名： | 时贵英 吴雅娟 倪红梅 |
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| 作者单位： | 东北石油大学计算机与信息技术学院,大庆163318 |
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| 摘 要： | 针对粒子群优化算法容易陷于局部最优的情况,将蚁群算法的信息素机制引入到粒子群算法中,保证了粒子间的多样性,从而有效克服了粒子群算法容易发生早熟停滞的缺陷。最后通过仿真实验证明了算法应用于软件测试的可行性和高效性。
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| 关 键 词： | 粒子群算法 蚁群算法 信息素机制 软件测试 |
An Improved Particle Swarm Optimization |
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| SHI Guiying,WU Yajuan,NI Hongmei.An Improved Particle Swarm Optimization[J].Journal of Changchun Institute of Optics and Fine Mechanics,2011(2):135-137. |
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| Authors: | SHI Guiying WU Yajuan NI Hongmei |
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| Affiliation: | (School of Computer＆Information Technology,Northeast Petroleum University,daqing 163318) |
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| Abstract: | Aiming at the condition that particle swarm optimization is easy to fall in local optima,the paper proposes an improved particle swarm optimization（PSO）.Pheromone mechanism of ant colony algorithm（ACO）is introduced into PSO（particle swarm algorithm）,the new algorithm can increase the diversity of particles and overcome the defect that PSO is easy to premature and stagnation.At last the simulation experiment proves the feasibility and efficiency of the algorithm in software testing. |
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| Keywords: | PSO ACO peromone mechanism software testing |
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