| 结合遗传算法的粒子群算法改进与应用 |
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| 引用本文： | 李森林,邓小武.结合遗传算法的粒子群算法改进与应用[J].怀化师专学报,2013(5):49-51. |
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| 作者姓名： | 李森林 邓小武 |
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| 作者单位： | 怀化学院计算机工程系,湖南怀化418008 |
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| 摘 要： | 标准粒子群算法（PSO）容易陷入局部最优解，导致收敛速度慢、效率低．文章结合遗传算法提出了改进的组合粒子群算法，在每次迭代后应用随机函数随机选择下一次迭代所使用的变异策略或交叉策略．由测试数据表明组合粒子群算法在求解TSP时性能上有很大提高．
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| 关 键 词： | 粒子群算法 旅行商问题 变异策略 |
Improvement and Application of PSO with GA |
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| LI Sen-lin,DENG Xiao-wu.Improvement and Application of PSO with GA[J].Journal of Huaihua Teachers College,2013(5):49-51. |
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| Authors: | LI Sen-lin DENG Xiao-wu |
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| Institution: | ( Department of Computer Engineering, Huaihua University, Huaihua Hunan 418008) |
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| Abstract: | Particle swarm optimization （PSO） always falls into local optimal solution, and causes slow convergence and low efficiency. The article puts forward a Combination of particle swarm optimization which combined with genetic algorithm, it adapts to random function to select the crossover strategy or mutation strategy for the next iteration randomly after iteration. The test data shows that Combination of particle swarm optimization is a better way in solving TSP. |
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| Keywords: | PSO TSP mutation strategy |
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