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    王旭坪

    • 教授     博士生导师   硕士生导师
    • 主要任职:Deputy Dean,School of Business,Dalian University of Technology
    • 性别:男
    • 毕业院校:大连理工大学
    • 学位:博士
    • 所在单位:系统工程研究所
    • 学科:管理科学与工程
    • 电子邮箱:wxp@dlut.edu.cn

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    Robust Aircraft Maintenance Routing Problem Using a Turn-Around Time Reduction Approach

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    论文类型:期刊论文

    发表时间:2021-01-10

    发表刊物:IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS

    卷号:50

    期号:12

    页面范围:4919-4932

    ISSN号:2168-2216

    关键字:Maintenance engineering; Delays; Aircraft; Atmospheric modeling; Aircraft manufacture; Robustness; Routing; Aircraft maintenance routing problem (AMRP); airline operations; robustness; turn-around time (TRT)

    摘要:This article discusses the problem of how to efficiently build aircraft routes that better withstand potential disruptions, such as bad weather, technical problems, and passenger delays. This optimization problem is called robust aircraft maintenance routing problem (RAMRP). There are three approaches in the literature to deal with the RAMRP, such as the buffer time allocation approach (BT), the departure retiming approach (DR), and the scenario-based stochastic programming approach (SSP). Most of the previous approaches have some shortcomings in terms of fleet productivity and delay absorption. In addition, the majority of the RAMRP models overlook maintenance regulations, which result in the generation of infeasible routes. In this article, RAMRP is investigated with two main objectives. First, a novel robustness approach, called the turn-around time reduction approach (TRTR), that avoids the shortcomings of the existing approaches, is incorporated into RAMRP. The second objective is to develop an RAMRP model that simultaneously considers all maintenance regulations. The effectiveness of the proposed RAMRP model along with the TRTR is demonstrated using real data from a major Middle Eastern airline. The results reveal an improved performance of the TRTR over the BT by about 3.43%-12.20% and 2.5%-13.58%, while handling the expected propagated delay costs and fleet productivity, respectively. In addition, the results show that the TRTR is better than the SSP by about 2.07%-18.82%, while minimizing the propagated delay costs. Therefore, the TRTR has a great potential to be implemented in the actual industry.