  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
