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改进量子粒子群算法在航材初始配置中的应用

田静,张恩豪,付维方   

  1. taptap下载安装安卓航空工程学院,天津300300
  • 收稿日期:2018-01-15 修回日期:2018-03-14 出版日期:2018-10-25 发布日期:2018-11-19
  • 作者简介:田静(1972—),女,辽宁兴城人,教授,博士,研究方向为飞机系统.

Application of improved quantum particle swarm algorithm in initial configuration of aircraft spare parts

TIAN Jing, ZHANG Enhao, FU Weifang   

  1. College of Aeronautical Engineering, CAUC, Tianjin 300300, China
  • Received:2018-01-15 Revised:2018-03-14 Online:2018-10-25 Published:2018-11-19

摘要: 针对量子粒子群优化算法在优化配置中存在过早收敛和全局寻优能力不完美的情况,从收缩扩张系数和进化因子方面进行改进。在航材配置模型构造方面,以改进系统保障率为目标函数的基础上引入成本变量,构建单位成本系统保障率最大的模型,选用波音首期设备清单为优化对象进行实例验证。实验证明,改进的量子粒子群算法求解结果更优,收敛速率更快。

关键词: 改进量子粒子群算法, 改进系统保障率, 单位成本, 首期设备清单

Abstract: Aiming at premature convergence and imperfect global optimization ability of quantum particle swarm optimal algorithm in optimal allocation, evolutionary factors and contraction expansion coefficient are improved. From the aspect of aircraft spare parts allocation model building, maximum unit cost system guarantee rate model is constructed, in which cost variables are introduced based on traditional goal of improving system assurance rate.Boeing's first stage equipment list is used as optimized object to validate the model, proving the better optimal result and faster convergence rate of the improved algorithm.

Key words: improved quantum particle swarm algorithm, improved system guarantee rate, unit cost, first stage equipment list

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