微粒群算法综述

Overview of particle swarm optimization

讨论微粒群算法的开发与应用。首先回顾从 1995年以来的开发过程 ,然后根据一些已有的测试结果对其参数设置进行系统地分析 ,并讨论一些非标准的改进手段 ,如簇分解、选择方法、邻域算子、无希望 /重新希望方法等。介绍了一些常用的测试函数 ,以及与其他演化算法的比较。最后讨论了一些已经开发和在将来有希望的领域中的应用。

The developments and applications related to particle swarm optimization (PSO) are discussed. Firstly, developments in the particle swarm optimization since 1995 are reviewed. Then parameter settings are analyzed systematically according to some existed testing results. Some improvement methods, such as cluster analysis, selection, neighborhood operator, no-hope/re-hope method, etc., are discussed. Some common test functions and the comparisons between PSO and others evolutionary algorithms are introduced. Finally, applications, both in the developed areas and the promising future application areas, are reviewed.