计算机工程与应用2012，Vol.48Issue(6)：46-48,3.DOI:10.3778/j.issn.1002-8331.2012.06.014
一种新的差分与粒子群算法的混合算法
New hybrid optimization based on differential evolution and particle swarm optimization
摘要
Abstract
To take advantage of different algorithms, a hybrid optimization algorithm is proposed based on the combination of Differential Evolution (DE) and Particle Swarm Optimization (PSO). At the last period of the hybrid optimization, a new population will be produced around the best position found by the PSO, and DE is carried out with this population. The hybrid optimization can deduce the computational work to some degree and has more chance to find the best solution in a better region. Numerical tests on some benchmark functions are conducted for the algorithm evaluation. The results show the higher precision and more probability to find the best solution.关键词
差分进化算法/粒子群优化算法/混合算法Key words
Differential Evolution (DE)/Particle Swarm Optimization(PSO)/hybrid algorithm分类
信息技术与安全科学引用本文复制引用
王志,胡小兵,何雪海..一种新的差分与粒子群算法的混合算法[J].计算机工程与应用,2012,48(6):46-48,3.
