Investigation of parallel particle swarm optimization algorithm with reduction of the search area

We consider a population based Particle Swarm Optimization (PSO) algorithm and a few modifications to increase quality of optimization. Several strategies are investigated to exchange data between processors in parallel algorithm. Experimental investigation is performed on Multiple Gravity Assist problem. The results are compared with original PSO.