A new particle swarm optimization algorithm for fuzzy optimization of armored vehicle scheme design

摘要: Armored vehicle design is a complex constrained optimization problem which often involves number of fuzzy and stochastic parameters. In this paper, model armored scheme presented, new particle swarm (PSO) algorithm proposed for effectively solving the problem. The uses variables to evaluate objective function constraints employs multiple ranking criteria define three global bests swarm, makes different quality particles learning from bests, thus search through solution space by means multi-criteria optimization. Experiment results show that our approach can achieve good with low computational costs.