【摘要】 提出一种分段式微粒群优化算法。该算法将所要搜索的区域分成若干段,首先在每一区段内搜索出区段的最优位置,然后将各区段的最优位置组成一微粒群,继续搜索全局最优位置。通过对5个常用标准测试函数进行优化计算,仿真结果表明:分段式微粒群优化算法能有效地搜索到全局最优解,具有比基本微粒群优化算法更快的搜索速度和更好的优化性能。更多还原

【Abstract】 A multi-sections particle swarm optimization algorithm(MSPSO) is proposed.The new(algorithm) assumes that the search area is divided into several sections.The best position of each section is found using particle swarm optimization algorithm and a new swarm that consists of the best positions of sections searches for the global best position by particle swarm optimization algorithm again.Then,both MSPSO and PSO are used to resolve five widely used test functions’ optimization problems.Results show that MSPSO has quicker convergence velocity and better optimization performance than PSO.更多还原