首页 | 本学科首页   官方微博 | 高级检索  
     

基于遗传退火算法的飞机定检原位工作流程优化
引用本文:吕晓峰,谢勇,席建峰,张勇亮.基于遗传退火算法的飞机定检原位工作流程优化[J].计算机与现代化,2012(7):25-29.
作者姓名:吕晓峰  谢勇  席建峰  张勇亮
作者单位:[1]海军航空工程学院兵器科学与技术系,山东烟台264001 [2]解放军91224部队,上海200235 [3]解放军91181部队,辽宁大连116000 [4]海军航空工程学院研究生管理大队,山东烟台264001
摘    要:将遗传算法(GA)应用于飞机定检原位工作流程优化中。首先,建立原位工作流程优化模型;其次,提出"排序调整法"来保证个体对应解符合工序约束;最后采用精英选择算子。模拟退火算子和自适应机制对基本遗传算法(SGA)进行改进。仿真结果表明,改进遗传算法在最优解搜索能力上较SGA有明显提高,克服了其容易"早熟"的不足;优化后原位工作完成时间较优化前缩短19.78%,验证了GA在解决定检工作流程优化问题上的适用性。

关 键 词:GA  飞机定检  原位工作  流程优化模型

Optimization of Plane' s Primary Periodic Maintenance Workflow Based on Genetic Annealing Algorithm
LUE Xiao-feng,XIE Yong,XI Jian-feng,ZHANG Yong-liang.Optimization of Plane' s Primary Periodic Maintenance Workflow Based on Genetic Annealing Algorithm[J].Computer and Modernization,2012(7):25-29.
Authors:LUE Xiao-feng  XIE Yong  XI Jian-feng  ZHANG Yong-liang
Affiliation:1. Department of Armament Science and Technology, Naval Aeronautical and Astronautical University, Yantai 264001, China; 2. The 91224 Army of PLA, Shanghai 200235, China; 3. The 91181 Army of PLA, Dalian 116000, China; 4. Graduate Students' Brigade, Naval Aeronautical and Astronautical University, Yantai 264001, China)
Abstract:Genetic algorithm(GA) is used to optimize plane's periodic maintenance primary workflow. Firstly, the model of pri- mary work is built. Secondly, the way of "adjusting the sequence" is proposed to ensure the solution of the individuals up to the limits of the work sequence. Finally, elitist operator, simulated annealing(SA) operator and adaptive mechanism are used to im- prove Simple Genetic Algorithm(SGA). The simulation results demonstrate that, the improved GA is much stronger in best-solu- tion search ability than SGA, and it overcomes its deficiency of being easy to "precocity" ; after optimization the finish time of primary work is shorter 19.78% than before, and proves that GA is good for the optimization of primary periodic maintenance workflow.
Keywords:GA  plane' s periodic maintenance  primary work  work/low optimization model
本文献已被 CNKI 维普 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号