连续空间二元粒子群算法理论研究综述

Research of continuing binary particle swarm optimization

连续空间的二元粒子群算法通过搜索空间与解空间相分离,在离散域及连续域优化问题中均得到较好的应用,但标准二元粒子群算法离散化机理存在的缺陷以及"探索"和"利用"的冲突均限制了二元粒子群算法更好的发展。从离散化机理的改进、算法的融合、协同控制以及算法的描述工具等方面入手,讨论了近年来对二元粒子群算法的若干改进及应用;最后评述了二元粒子群算法未来的研究方向和主要研究内容。

Separating the searching space from the solution space,the binary particle swarm optimization has good performance in the discrete combinational optimization problems and continuous optimization problems.However,the drawbacks that easy to fall into the local optimization and the discrete mechanism still exist.Starting with the improvement of the discrete mechanism and the fusion of the algorithm as well as the algorithm description tool,this paper discussed a series of schemes on improving the binary particle swarm optimization,and also provided the new applications.Finally,it presented some remarks on the futher research.