Author:

Keywords:

Model enhancement, Aircraft maintenance, Stochastic optimization, Social Sciences, Science & Technology, Technology, Management, Operations Research & Management Science, Business & Economics, LINE MAINTENANCE, OPTIMIZATION, SIMULATION, PRICE, Operations Research, 40 Engineering, 46 Information and computing sciences, 49 Mathematical sciences

Abstract:

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 labour 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 labour costs when stochasticity is introduced in the aircraft arrival times.