A bi-objective aircraft maintenance routing problem based on flying hours to efficient use of available fleet

IF 2.2 Q3 MANAGEMENT Journal of Facilities Management Pub Date : 2022-07-26 DOI:10.1108/jfm-02-2022-0018
Hiwa Esmaeilzadeh, Alireza Rashidi Komijan, H. Kazemipoor, M. Fallah, R. Tavakkoli-Moghaddam
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Abstract

Purpose The proposed model aims to consider the flying hours as a criterion to initiate maintenance operation. Based on this condition, aircraft must be checked before flying hours threshold is met. After receiving maintenance service, the model ignores previous flying hours and the aircraft can keep on flying until the threshold value is reached again. Moreover, the model considers aircraft age and efficiency to assign them to flights. Design/methodology/approach The aircraft maintenance routing problem (AMRP), as one of the most important problems in the aviation industry, determines the optimal route for each aircraft along with meeting maintenance requirements. This paper presents a bi-objective mixed-integer programming model for AMRP in which several criteria such as aircraft efficiency and ferrying flights are considered. Findings As the solution approaches, epsilon-constraint method and a non-dominated sorting genetic algorithm (NSGA-II), including a new initializing algorithm, are used. To verify the efficiency of NSGA-II, 31 test problems in different scales are solved using NSGA-II and GAMS. The results show that the optimality gap in NSGA-II is less than 0.06%. Finally, the model was solved based on real data of American Eagle Airlines extracted from Kaggle datasets. Originality/value The authors confirm that it is an original paper, has not been published elsewhere and is not currently under consideration of any other journal.
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基于飞行时数的双目标机队维修路线问题
目的所提出的模型旨在将飞行时间作为启动维护操作的标准。基于这种情况,在达到飞行时间阈值之前,必须对飞机进行检查。在接受维修服务后,该模型忽略了以前的飞行时间,飞机可以继续飞行,直到再次达到阈值。此外,该模型考虑了飞机的年龄和效率,将其分配给飞行。设计/方法/方法飞机维修路线问题(AMRP)是航空业最重要的问题之一,它决定了每架飞机的最佳路线,同时满足维修要求。本文提出了一个AMRP的双目标混合整数规划模型,该模型考虑了飞机效率和运输航班等几个标准。作为求解方法,使用了ε约束方法和非支配排序遗传算法(NSGA-II),包括一种新的初始化算法。为了验证NSGA-II的有效性,使用NSGA-II和GAMS解决了31个不同规模的测试问题。结果表明,NSGA-II的最优性差距小于0.06%。最后,基于从Kaggle数据集中提取的美国鹰航空公司的真实数据对模型进行了求解。原创性/价值作者确认这是一篇原创论文,尚未在其他地方发表,目前也没有任何其他期刊在考虑中。
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来源期刊
CiteScore
4.30
自引率
15.80%
发文量
56
期刊介绍: Journal of Facilities Management is a strategic level journal for Heads of Facilities and Corporate Real Estate. Guided by its international and expert Editorial Board, Journal of Facilities Management publishes high-quality, authoritative, and detailed analysis, briefings and case studies on how facilities can and do play a vital part in helping deliver corporate strategy. This quarterly publication features contributions from leading practitioners and thinkers in the field of Facilities Management, from some of the leading companies, government institutions, and universities in the world. The journal features a combination of theoretical and practical articles, complemented by a wide range of case studies and regular features, identifying key implications for senior practitioners in Facilities Management.
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