Charting the future of pilots: maximizing airline workforce efficiency through advanced analytics

Burak Cankaya, Bulent Erenay, Eyyub Kibis, Aaron Glassman and Dursun Delen ()
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Burak Cankaya: Embry-Riddle Aeronautical University
Bulent Erenay: Northern Kentucky University
Eyyub Kibis: Montclair State University
Aaron Glassman: Embry-Riddle Aeronautical University
Dursun Delen: Oklahoma State University

Operational Research, 2024, vol. 24, issue 3, No 16, 32 pages

Abstract: Abstract Pilots and aircraft are among the most valuable assets of an airline. Buying aircraft and hiring pilots are crucial strategic decisions companies must oversee for sustainability. The cost of buying, selling, leasing, and long production times for aircraft challenge companies in making optimal long-term decisions. Union rules, pilot shortages, pilot surplus, and the cost of employing an excessive number of pilots are factors complicating the workforce planning for airline companies worldwide. Under these volatile and conflicting circumstances, many companies cannot strategically plan for the planning of pilots to aircraft to meet short-term tactical decisions against mid/long-term company strategies. In this study, our objective is to optimize long-term crew planning by minimizing the total crew cost considering captain promotions and new hires, without compromising the pilot experience. A mixed integer programming model is developed to solve the long-term airline crew planning problem. Realistic business scenarios are used to determine the optimal pilot hiring and promotion patterns for both high-and low-demand scenarios. The results show that the proposed optimization method significantly reduces crew costs without compromising the pilot experience in various demand and cost scenarios. The mathematical model, the realistic business scenarios, and the business insights for airlines are deemed novel contributions to the pertinent literature and industry practices.

Keywords: Crew planning; Manpower planning; Airline workforce planning; Mathematical optimization; Pilot optimization; Aviation business analytics; Aviation strategic decision making (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s12351-024-00861-6

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