[Show abstract][Hide abstract] ABSTRACT: In this research, we focused on multiobjective nonlinear programming problems and proposed a new MOrPSO technique which is accuracy for in applying the interactive fuzzy satisficing method. In particular, considering the features of augmented minimax problems solved in the interactive fuzzy satisficing method, we incorporated use of external archives, reduction of archives and the limitation of threshold value. Finally, we showed the efficiency of the proposed MOrPSO by applying it to numerical examples.
[Show abstract][Hide abstract] ABSTRACT: Particle swarm optimization (PSO) was proposed by Kennedy et al. as a general approximate solution method for nonlinear programming problems. Its efficiency has been shown, but there have been left some shortcomings of the method. Thus, the authors proposed a revised PSO (rPSO) method incorporating the homomorphous mapping and the multiple stretching in order to cope with these shortcomings. In this paper, we construct an interactive fuzzy satisficing method for multiobjective nonlinear programming problems based on the rPSO. Furthermore, 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. Finally, we show the efficiency of the proposed method by applying it to numerical examples
Computational Intelligence in Multicriteria Decision Making, IEEE Symposium on; 05/2007