A mathematical programming model for aircraft fleet management

Abstract

Airlines operate in a business environment with very low profit margins and fuel prices greatly affect the profitability of airlines. In fact, depending on the type and age of aircraft, the fuel cost can range between 20-25% of the total operating expenses. While crew costs do not typically change with the age of the aircraft, maintenance costs do, as there are more intensive and costly events occurring at later stages of an aircraft's life cycle. Coupled with their higher operating costs, older aircraft are therefore more likely to be favored for replacement if the fuel prices increase at the rates expected. It is clear from the growth in the airline market that airlines will need appropriate fleet replacement and acquisition strategies to cope with the increasing demand for air travel while succesfully competing in a low profit margin industry that is becoming increasingly liberalized. There are very few articles that jointly considers the subject of fleet planning, aircraft procurement and aircraft phase-out as these decisions are based on strategic plans and decisions and therefore require very confidential data. Nevertheless, the current market situation as reported by various industry leaders has been analyzed. Using the integer linear programming approach existing in the literature, a new model was designed to address the issues that are sometimes over simplified and sometimes unnecessarily complicated. The model made certain improvements to the existing models in literature but did not answer all of the weaknesses noted. For data collection and case study in this research, a carrier based in Istanbul, Turkey was used to design and validate the model. IBM-ilog Studio IDE 12.7.1 software with CPLEX optimization engine was used to program and run the model. Running this model in the case study showed that the model uses both purchasing and leasing options to answer the increasing demand. The model

was then modified for wide-body aircraft and the model prefers fuel efficient new generation aircraft over the existing type. Sensitivity analysis of the model was performed. The results showed that the current solutions were not very sensitive and therefore robust against the increases in IRR rates. Direction for future research was then proposed to cover the shortcomings of the model that was presented in the thesis.