期刊
APPLIED INTELLIGENCE
卷 37, 期 4, 页码 520-526出版社
SPRINGER
DOI: 10.1007/s10489-012-0345-0
关键词
Armored vehicle design; Particle swarm optimization (PSO); Fuzzy optimization; Ranking criteria
资金
- National Natural Science Foundation of China [61105073, 61020106009]
Armored vehicle design is a complex constrained optimization problem which often involves a number of fuzzy and stochastic parameters. In this paper, a fuzzy optimization problem model of armored vehicle scheme design is presented, and a new particle swarm optimization (PSO) algorithm is proposed for effectively solving the problem. The problem model uses fuzzy variables to evaluate the objective function and constraints of the problem. The algorithm employs multiple ranking criteria to define three global bests of the swarm, makes different quality particles learning from different global bests, and thus search effectively through the solution space by means of multi-criteria optimization. Experiment results show that our approach can achieve good solution quality with low computational costs.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据