基于遗传算法的飞机维修计划编制优化方案
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  • 英文篇名:Optimization Solution of Aircraft Maintenance Plan based on Genetic Algorithm
  • 作者:王孝琨 ; ; 朱璘珺 ; 张意文
  • 英文作者:Wang Xiaokun;Cui Ke;Zhu Linjun;Zhang Yiwen;Marketing & Customer Support Department,Shanghai Aircraft Customer Service Co.,Ltd.;Maintenance & Engineering Department,Air China Cargo Co.,Ltd.;Maintenance Department,China Eastern Airlines Technology Co.,Ltd.;
  • 关键词:遗传算法 ; 粒子群算法 ; 维修成本 ; 飞机维修计划
  • 英文关键词:genetic algorithm;;particle swarm algorithm;;maintenance cost;;maintenance plan
  • 中文刊名:JXKX
  • 英文刊名:Mechanical Science and Technology for Aerospace Engineering
  • 机构:中国商飞上海飞机客户服务有限公司市场与客户支援部;中国国际货运航空有限公司机务工程部;中国东方航空技术有限公司维修部;
  • 出版日期:2017-09-15
  • 出版单位:机械科学与技术
  • 年:2017
  • 期:v.36
  • 语种:中文;
  • 页:JXKX2017S1010
  • 页数:5
  • CN:S1
  • ISSN:61-1114/TH
  • 分类号:53-57
摘要
针对航空公司维修计划编制现状及重要性,分析飞机维修计划编制流程及涉及要素,建立基于维修成本的飞机维修计划编制优化模型,并采用遗传算法对模型进行求解。结果表明,建立的模型和求解算法切实可行,可用于各类型航空公司飞机维修计划的编制和优化,且优化结果满足航空公司实际需求。同时对比分析可知,遗传算法比粒子群算法在求解效果上有优越性。
        This paper analyses the process and elements relative to aircraft maintenance plan against the conditions and importance in Chinese airlines. And an optimization model is established on basis of maintenance cost. Then genetic algorithm is introduced and proposed for solving the model. The simulation result verifies that the model and algorithm are feasible. This solution is used to write and optimize aircraft maintenance plan. In fact the optimization result meets demands of airlines better. Meanwhile it makes an analysis that genetic algorithm is better than particle swarm algorithm in the solution.
引文
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