Abstract
In recent years, particle swarm optimization (PSO) proposed by Kennedy
et al. has been widely used as a general approximate solution method for optimization
problems. The authors proposed a revised PSO (rPSO) method incorporating the
homomorphous mapping and the multiple stretching technique in order to cope with
shortcomings of PSO and showed its efficiency for nonlinear programming problems.
In this paper, we construct an interactive fuzzy satisficing method for multiobjective
nonlinear programming problems based on the rPSO. In order to obtain better
solutions in consideration of the property of multiobjective programming problems,
we incorporate the direction to nondominated solutions into the rPSO. Furthermore,
the efficiency of the proposed method (MOrPSO) is shown through applications to
numerical examples.
