Particle swarm optimization with dynamic-population for multi-peak searching
多峰搜索的动态微粒群算法

A class of dynamic-population particle swarm optimization for searching peaks of some multi-peak functions was proposed. This algorithm transformed all peaks of multi-peak problems into those peaks equally high by functional transformation, in order to find all peaks with the same probability. During the searching the size of particle swarm could be tuned to get any initial size of swarm. So it could solve the problem of determining swarm size because the number of peaks of the given multi-peak function could not be obtained in standard particle swarm optimization. The experiments manifest that the algorithm can search peaks of function as much as possible.