摘要
分析了战时军械紧急调运的特点,指出了已有相关研究的局限性:①没有考虑军械紧急调运中存在的不确定性;②模型优化算法的实现较为复杂。针对这两点不足,将智能优化算法PSO与MonteCarlo仿真进行融合,提出了基于仿真的军械紧急调运决策模型,并依据模型较好地解决不确定环境下的军械紧急调运的决策优化问题。结合一个仿真算例,通过对比分析,证明了采用基于仿真的模型得到的调运决策更为合理、可信。
The characteristic of urgent transportation of ordnance in wartime was analysed, limitation of the related research before was pointed out： ①Uncertainty in the actual process of ordnance transportation is not considered; ②The optimization algorithm is complex. Aiming at these two shortages, Particle Swarm Optimization and Monte Carlo simulation was integrated, and a decision-making model of ordnance transportation based on simulation was established and the problem of ordnance transportation was intelligently optimized. Through an example, the validity of model is proved.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2007年第3期683-686,共4页
Journal of System Simulation
关键词
军械紧急调运
决策模型
PSO算法
MONTE
Carlo仿真
不确定性
urgent transportation of ordnance
decision-making model
Particle Swarm Optimization
Monte Carlo simulation
uncertainty
