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基于改进PSO和DE的混合算法 被引量:18

Hybrid Algorithm Based on Improved PSO and DE
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摘要 研究粒子群优化(PSO)算法和差分进化(DE)算法的优缺点,通过改进PSO算法并与DE算法混合,得到一种双种群的新型混合全局优化算法。经过对5个标准测试函数的大量实验计算表明,该算法能有效克服PSO算法和DE算法的缺陷,使寻优精度有较大改进,在高维情况下表现更加突出。 In accordance with the respective advantages and disadvantages of Particle Swarm Optimization(PSO) algorithm and Differential Evolution(DE) algorithm,a novel hybrid algorithm is achieved through the improvement of Particle Swarm Optimization(PSO) algorithm and mixture with Differential Evolution(DE) algorithm.Massive experiments of five standard benchmark functions in five different dimensions suggest that this novel hybrid algorithm effectively overcomes the respective disadvantages of PSO algorithm and DE algorithm.It produces a conspicuous effect,which results in satisfactory outcome in experiments especially in high dimension.
出处 《计算机工程》 CAS CSCD 北大核心 2010年第10期233-235,共3页 Computer Engineering
基金 广西自然科学基金资助项目(桂科自0640067)
关键词 粒子群优化算法 差分进化算法 混合算法 Particle Swarm Optimization(PSO) algorithm Differential Evolution(DE) algorithm hybrid algorithm
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