Using integer programming for airport service planning in staff scheduling

W. H. Ip, Sai Ho Chung, George Ho

Research output: Journal article publicationJournal articleAcademic researchpeer-review

4 Citations (Scopus)

Abstract

Reliability and safety in flight is extremely necessary and that depend on the adoption of proper maintenance system. Therefore, it is essential for aircraft maintenance companies to perform the manpower scheduling efficiently. One of the objectives of this paper is to provide an Integer Programming approach to determine the optimal solutions to aircraft maintenance planning and scheduling and hence the planning and scheduling processes can become more efficient and effective. Another objective is to develop a set of computational schedules for maintenance manpower to cover all scheduled flights. In this paper, a sequential methodology consisting of 3 stages is proposed. They are initial maintenance demand schedule, the maintenance pairing and the maintenance group(s) assignment. Since scheduling would split up into different stages, different mathematical techniques have been adopted to cater for their own problem characteristics. Microsoft Excel would be used. Results from the first stage and second stage would be inputted into integer programming model using Microsoft Excel Solver to find the optimal solution. Also, Microsoft Excel VBA is used for devising a scheduling system in order to reduce the manual process and provide a user friendly interface. For the results, all can be obtained optimal solution and the computation time is reasonable and acceptable. Besides, the comparison of the peak time and non-peak time is discussed.
Original languageEnglish
Pages (from-to)85-92
Number of pages8
JournalInternational Journal of Engineering Business Management
Volume2
Issue number2
DOIs
Publication statusPublished - 1 Jan 2010

Keywords

  • Aircraft
  • Airport service
  • Maintenance
  • Manpower scheduling

ASJC Scopus subject areas

  • Organizational Behavior and Human Resource Management
  • Management Science and Operations Research

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