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.