A dissipative particle swarm optimization

Computer Science – Neural and Evolutionary Computing

Scientific paper

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Proceedings of the 2002 Congress on Evolutionary Computation, 2002. Volume: 2, On page(s): 1456-1461

Scientific paper

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

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