Article ID: | iaor201527317 |
Volume: | 246 |
Issue: | 2 |
Start Page Number: | 661 |
End Page Number: | 673 |
Publication Date: | Oct 2015 |
Journal: | European Journal of Operational Research |
Authors: | Demeulemeester Erik, Belin Jeroen, De Bruecker Philippe, Van den Bergh Jorne |
Keywords: | transportation: air, manufacturing industries, heuristics, stochastic processes, combinatorial optimization |
This paper presents a heuristic approach to optimize staffing and scheduling at an aircraft maintenance company. The goal is to build robust aircraft maintenance personnel rosters that can achieve a certain service level while minimizing the total labor costs. Robust personnel rosters are rosters that can handle delays associated with stochastic flight arrival times. To deal with this stochasticity, a model enhancement algorithm is proposed that iteratively adjusts a mixed integer linear programming (MILP) model to a stochastic environment based on simulation results. We illustrate the performance of the algorithm with a computational experiment based on real life data of a large aircraft maintenance company located at Brussels Airport in Belgium. The obtained results are compared to deterministic optimization and straightforward optimization. Experiments demonstrate that our model can ensure a certain desired service level with an acceptable increase in labor costs when stochasticity is introduced in the aircraft arrival times.