Acquisition of New Aircraft with Probabilistic Dynamic Programming

Abstract

This study deals with an aircraft acquisition decision model to tackle the stochastic demand of the air transportation system. Probabilistic dynamic programming is applied to develop an optimization model with the aim to maximize the operational profit of the airline company. Correspondingly, a probable phenomenon is defined to comprehend the uncertain state variables so that the targeted level of service by the airline company could be met satisfactorily. The proposed probabilistic dynamic programming model is then converted into a non-linear programming model as the objective function and the constraints have non-linear expression with respect to the decision variables. Later, the proposed model and the solution method are examined with an illustrative case study to determine the number and the types of new aircraft that should be purchased at every time period. The results show that the proposed methodology is viable in providing the optimal solution.