Abstract: 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.

Key words: Particle Swarm Optimization(PSO) algorithm, Differential Evolution(DE) algorithm;, hybrid algorithm

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。

关键词: 粒子群优化算法, 差分进化算法, 混合算法

CLC Number: 

• TP312