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.