A dissipative particle swarm optimization
Neural and Evolutionary Computing
2007-05-23 v2
Abstract
A dissipative particle swarm optimization is developed according to the self-organization of dissipative structure. The negative entropy is introduced to construct an opening dissipative system that is far-from-equilibrium so as to driving the irreversible evolution process with better fitness. The testing of two multimodal functions indicates it improves the performance effectively
Keywords
Cite
@article{arxiv.cs/0505065,
title = {A dissipative particle swarm optimization},
author = {Xiao-Feng Xie and Wen-Jun Zhang and Zhi-Lian Yang},
journal= {arXiv preprint arXiv:cs/0505065},
year = {2007}
}
Comments
Proceedings of the 2002 Congress on Evolutionary Computation, 2002. Volume: 2, On page(s): 1456-1461