Experimental study for multi-objective PSO with single objective guide selection

Multi-objective particle swarm optimization has two different points from single objective one. The first point is guide position selection methods for personal best and global best. The second one is the usage of an archive to preserve good positions for Pareto optimal set. In this paper, we consider a guide selection problem in multiobjective particle swarm optimization. A selection method for the personal best that depends on one objective function among plural objective functions is presented. Then, a selection method for the global best that selects among the archived position due to one objective function is presented. The performances of the proposed methods are evaluated by the benchmark problems for the evolutionary multiobjective optimization algorithms.