2412 非劣解の多様性を考慮した多目的Particle Swarm Optimization(OS6-1 近似最適化(I))

概要

論文の詳細を見る
The objectives of the Multi-Objective Evolutionary Algorithms (MOEA) are summarized as follows: (1) To find the pareto optimal solutions, (2) To find the pareto optimal solutions as diverse as possible. To achieve these objectives by the PSO for the single objective problems, we propose how to define the g-best in the swarm without introducing some new parameters. That is, one particle among the non-inferior solutions is selected as the g-best to achieve the divesity among the non-inferior solutions. The relative distance in the objective space is utilized to select the g-best among the non-inferior solutions. Additionally, some particles among the non-inferior solutions are also selected as the g-best of the inferior solutions to find the pareto optimal solutions. The absolute distance in the objective space is utlized to select the g-best of the inferior solutions. We also show the geometical interpretation about the movement of particles. The validity of proposed approach is examined through typical numerical examples.
社団法人日本機械学会の論文
2007-10-30