Repulsive Particle Swarm Method on Some Difficult Test Problems of Global Optimization

Abstract

I. Introduction: Optimization of non-convex (multi-modal) functions is the subject matter of research in global optimization. During the 1970's or before only little work was done in this field, but in the 1980's it attracted the attention of many researchers. Since then, a number of methods have been proposed to find the global optima of non-convex (multi-modal) problems of combinatorial as well as continuous types. Among these methods, genetic algorithms, simulated annealing, particle swarm, ants colony, tunneling, taboo search, etc. have been quite successful as well as popular.

Cite this paper

@inproceedings{Mishra2006RepulsivePS, title={Repulsive Particle Swarm Method on Some Difficult Test Problems of Global Optimization}, author={Sk Mishra}, year={2006} }