装备维修过程中备件布局的多目标优化决策  

MULTI-OBJECTIVE OPTIMISATION DECISION FOR SPARE PARTS LAYOUT IN EQUIPMENT MAINTENANCE PROCESS

作　　者：郭璐[1] 杨云[1] 王崴[1] 刘晓卫[1] 

机构地区：[1]空军工程大学防空反导学院,陕西西安710051

出　　处：《计算机应用与软件》2016年第10期233-237,共5页Computer Applications and Software

基　　金：国家自然科学基金项目(51075395);国家高技术研究发展计划项目(2013AA040604)

摘　　要：为保证在装备维修过程中能精确、及时、高效地取用备件,提出备件车装载布局优化问题。针对该问题建立备件布局优化数学模型,以备件车承载容积、载重量及重心等为约束条件,综合考虑备件车空间利用率、备件合重心对行车安全性的影响和备件取用效率为目标函数。根据备件布局模型的特殊性,基于模拟退火算法的思想,将其与带压缩因子的粒子群优化算法结合,应用于实例中求解布局方案,并将此混合算法的计算结果与基本粒子群优化算法的计算结果进行了比较。结果表明,使用混合粒子群优化算法可以获得较好的装载布局优化方案,达到充分利用备件车装载空间、安全性好和取用效率高的目的。In order to ensure accurate,timely and efficient spare parts access in equipment maintenance process,we put forward the problem of loading and layout optimisation for spare parts car. In light of this issue we built the mathematical model of spare parts layout optimisation,took the bearing volume,load capacity and gravity centre of the spare car as the constraint conditions,and took into account comprehensively the space utilisation of spare parts car,the influence of spare parts' combined gravity centres on driving safety and the spare parts' access efficiency as the objective functions. According to the particularity of spare parts layout model and based on the idea of simulated annealing algorithm,we combined them with the particle swarm optimisation with constrict factor and applied it in actual example to calculate the layout solution. We also compared the calculation result of this hybrid algorithm with that of the basic particle swarm optimisation algorithm. Results showed that to use hybrid particle swarm optimisation algorithm can obtain better loading and layout optimisation scheme,it achieves the goals of making full use of spare car's loading space,good in safety and high access efficiency.

关 键 词：备件车 布局 粒子群算法 模拟退火算法 压缩因子 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]