Talk: A Stochastic Optimization Model for Fleet Assignment under Uncertainty Conditions

Abstract

The variability in operational times has a great impact on aircraft scheduling. This work analyzes fleet assignment, considering the stochastic behavior of operational times. To solve the Fleet Assignment Problem (FAP), we propose a stabilized column generation problem, applying a set of specialized auxiliary shortest path models, based on lineal and dynamic programming (k-Shortest Path Problem with Resource Constraint - SPPRC). Finally, employing a Monte Carlo simulation, the On - Time Performance (OTP) of the fleet assignment is evaluated in specific scenarios.