Particle Swarm Optimization for Multi-objective Systems with Interval Parameters
含区间参数多目标系统的微粒群优化算法

Optimization problems with uncertainties are a kind of familiar and complicated optimization problems,and most of the existing methods only deal with the case of a single-objective function.To solve multi-objective optimization problems with interval parameters by particle swarm optimization,a multi-objective particle swarm optimization algorithm based on probable dominance is proposed in this paper.In the algorithm,the probable dominance and the a intervals are presented to compare the quality of solutions and select the globally optimal particles,respectively.A novel strategy for updating locally optimal particles and exterior archive are put forward.The feasibility of the proposed algorithm is validated by simulation results.