| 基于差分演化的粒子群算法 |
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| 引用本文： | 段玉红,高岳林. 基于差分演化的粒子群算法[J]. 计算机仿真, 2009, 26(6): 212-215,245 |
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| 作者姓名： | 段玉红 高岳林 |
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| 作者单位： | 1. 宁夏大学数学与计算机学院,宁夏,银川,750021
2. 北方民族大学信息与系统科学研究所,宁夏,银川,750021 |
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| 摘 要： | 粒子群优化算法是一种简单有效的随机全局优化算法.但粒子群优化算法有易陷入局部极值点,进化后期收敛速度慢,精度较差的缺点.为了改进粒子群优化算法,将差分演化算法融合到粒子群优化算法中,在算法中,将粒子每代的所有局部最优位置进行变异、杂交、选择操作,提出了基于差分演化的粒子群算法.使粒子群算法和差分演化的探测和开发能力得到有效利用与平衡,提高了求解进度和效率,并通过仿真验证算法的性能优于带线性递减权重的粒子群优化算法和差分演化算法.
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| 关 键 词： | 粒子群优化 差分演化 杂交 变异 |
A Particle Swarm Optimization Algorithm Based on Differential Evolution |
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| DUAN Yu-hong,GAO Yue-lin. A Particle Swarm Optimization Algorithm Based on Differential Evolution[J]. Computer Simulation, 2009, 26(6): 212-215,245 |
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| Authors: | DUAN Yu-hong GAO Yue-lin |
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| Affiliation: | 1.School of Mathematics and Computer;Ningxia University;Yinchuan Ningxia 750021;China;2.Institute of Information and System Computation Science;North National University;China |
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| Abstract: | Particle swarm optimization is a simple stochastic global optimization algorithm,but it is easy to fall into partial extreme point,its convergence rate is low in the later evolution period,and the precision is low.For improving the particle swarm optimization algorithm,in this paper,differential evolution is involved into PSO algorithm.Handling the current optimum positions with mutation and crossover,and a particle swarm optimization algorithm based on differential evolution(DPSO) is proposed.In this algor... |
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| Keywords: | Particle swarm optimization Differential evolution Crossover Mutation |
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