基于改进粒子群算法的野战油库选址优化  

Improved Particle Swarm Optimization Based on Field Oil Depot Site

作　　者：张卫明[1] 周庆忠[1] 黎武[1] 

机构地区：[1]后勤工程学院军事油料应用与管理工程系,重庆401311

出　　处：《兵器装备工程学报》2016年第8期84-87,共4页Journal of Ordnance Equipment Engineering

摘　　要：针对标准粒子群算法容易陷入局部最优,提出了改进粒子群算法;对粒子的自适应性和惯性权重进行改进,建立了野战油料选址模型;通过仿真,发现改进粒子群算法克服了标准粒子群算法容易陷入局部最优的问题,且寻优能力强,对部队的野战油库选址具有指导作用。For that standard particle swarm algorithm is easy to fall into local optimal,the improved particle swarm optimization（ PSO） algorithm was proposed. The adaptability and inertia weight of particles were improved,and field oil location model were established. Through simulation,we found that the improved particle swarm algorithm overcomes that the standard particle swarm algorithm is easy to fall into local optimum,and its optimization ability is strong,and the force field is of important guiding significance for oil storage location.

关 键 词：改进粒子群算法 野战油库 选址优化 

分 类 号：E233[军事—军事理论]