| 自适应变异粒子群优化算法 |
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| 引用本文： | 黄继红,苏守宝,马艳,陈振伟. 自适应变异粒子群优化算法[J]. 皖西学院学报, 2010, 26(2): 27-30 |
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| 作者姓名： | 黄继红 苏守宝 马艳 陈振伟 |
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| 作者单位： | 皖西学院,计算机科学技术系,安徽,六安,237012 |
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| 基金项目： | 安徽省自然科学基金，安徽高校省级自然科学重点项目 |
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| 摘 要： | 提出了一种自适应变异粒子群优化算法,该算法通过遗传变异提高种群多样性的方法使算法增强持续搜索能力,解决了PSO算法的早熟收敛问题。采用标准测试函数进行仿真实验,结果表明：提出的算法具有提高局部最优值的能力,且优化精度更高。
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| 关 键 词： | 粒子群优化 遗传算法 变异 自适应性 |
Particle Swarm Optimization Algorithm with Adaptive Mutation |
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| Huang Ji-hong,Su Shou-bao,Ma Yan,Chen Zhen-wei. Particle Swarm Optimization Algorithm with Adaptive Mutation[J]. Journal of Wanxi University, 2010, 26(2): 27-30 |
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| Authors: | Huang Ji-hong Su Shou-bao Ma Yan Chen Zhen-wei |
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| Affiliation: | Huang Ji-hong,Su Shou-bao,Ma Yan,Chen Zhen-wei (Department of Computer Science , Technology,West Anhui University,Lu'an 237012,China) |
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| Abstract: | A particle swarm optimization algorithm with adaptive mutation(AMPSO) is presented in this paper.The algorithm of genetic variation through increased population diversity means to make the algorithm of continuing the search capabilities of the PSO algorithm to overcome the phenomenon of premature convergence.Adopting well-known benchmark test functions Rosenbork function simulation experiments,it shows that the proposed algorithm has a strong breakthrough in the capacity of local optimal value and optimal p... |
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| Keywords: | particle swam optimization genetic algorithm mutation adaptive |
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