A mathematical model and algorithms for the aircraft hangar maintenance scheduling problem

Yichen Qin, Z. X. Wang, Felix T.S. Chan, S. H. Chung, T. Qu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

17 Citations (Scopus)

Abstract

An aircraft hangar maintenance scheduling problem is studied, motivated by the aircraft heavy maintenance conducted in a hangar operated by an independent maintenance service company. The aircraft hangar maintenance scheduling problem in such context consists of determining a maintenance schedule with minimum penalty costs in fulfilling maintenance requests, and a series of hangar parking plans aligned with the maintenance schedule through the planning period. A mixed-integer linear programming (MILP) mathematical model, integrating the interrelations between the maintenance schedule and aircraft parking layout plans, is presented at first. In the model, the variation of parking capacity of the maintenance hangar and the blocking of the aircraft rolling in and out path are considered. Secondly, the model is enhanced by narrowing down the domain of the time-related decision variables to the possible rolling in and out operations time of each maintenance request. Thirdly, to obtain good quality feasible solutions for large scale instances, a rolling horizon approach incorporating the enhanced mathematical model is presented. The results of computational experiments are reported, showing: (i) the effectiveness of the event-based discrete time MILP model and (ii) the scalability of the rolling horizon approach that is able to provide good feasible solutions for large size instances covering a long planning period.

Original languageEnglish
Pages (from-to)491-509
Number of pages19
JournalApplied Mathematical Modelling
Volume67
DOIs
Publication statusPublished - 1 Mar 2019

Keywords

  • Aircraft maintenance scheduling
  • Event-based model
  • Hangar parking layout planning
  • Mixed-integer linear programming
  • Rolling horizon approach

ASJC Scopus subject areas

  • Modelling and Simulation
  • Applied Mathematics

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