A model enhancement heuristic for building robust aircraft maintenance personnel rosters with stochastic constraints

A model enhancement heuristic for building robust aircraft maintenance personnel rosters with stochastic constraints

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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: , , ,
Keywords: transportation: air, manufacturing industries, heuristics, stochastic processes, combinatorial optimization
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 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.

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