Description: PARTICLE SWARM OPTIMIZER IN NOISY AND
CONTINUOUSLY CHANGING ENVIRONMENTS
ABSTRACT
In this paper we study the performance of the recently proposed
Particle Swarm optimization method in the presence
of noisy and continuously changing environments. Experimental
results for well known and widely used optimization
test functions are given and discussed. Conclusions for
its ability to cope with such environments as well as real–
life applications are also derived.
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