In this paper, two sub-swarms substituting particle swarm optimization algorithm (TSSPSO) is proposed. The algorithm parameters are analyzed and the iteration equations are amended.
提出一种两群替代微粒群优化算法(TSSPSO)，并对算法参数进行分析和对算法方程进行修正。
On the basis of analyzing the particle swarm optimization and introducing the idea of sub-swarms, a particle swarm optimization algorithm with dynamic sub-swarms (DPSO) is proposed.
在分析基本微粒群优化算法的基础上，引进分群思想，提出了一种动态分群的微粒群优化算法(DPSO)。
According to still existing problem of Quantum-behaved Particle Swarm Optimization (QPSO), a new QPSO with two Particle Swarms based on public history researching side-by-side (TPHQPSO) is presented.
针对量子粒子群算法存在的问题，设计基于公共历史的两种群并行搜索的量子粒子群算法。
According to still existing problem of Quantum-behaved Particle Swarm Optimization (QPSO), a new QPSO with two Particle Swarms based on public history researching side-by-side (TPHQPSO) is presented.
针对量子粒子群算法存在的问题，设计基于公共历史的两种群并行搜索的量子粒子群算法。
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