Betreuer: Marlon Braun, Fabian Kern, Hartmut Schmeck
Forschungsgruppe: Effiziente Algorithmen
Partner: Hendrik Meyer, Deutsches Zentrum für Luft- und Raumfahrt
Abschlussarbeitsstatus: In Bearbeitung
Beginn: 01. Januar 2016
Abgabe: 30. Juni 2016
This thesis addresses task-centric aircraft maintenance planning optimization in the context of research projects at the German Aerospace Center (DLR). Therefore, the aircraft maintenance planning problem (AMPP) is presented for determining optimal maintenance schedules for a fleet of aircraft that operates between multiple airports with limited maintenance capacities. In contrast to the traditional block check maintenance program, an equivalent task-based maintenance program underlies the AMPP. In order to fulfill the requirements of two distinct use cases for aircraft maintenance planning optimization at DLR, two mathematical models are developed and integrated into the aircraft technology and operations benchmark system (AIRTOBS). Those models extend the existing aircraft maintenance planning model (AIRMAP) to a fleet level and allow for the application of exact solving methods. Additionally, a problem-specific genetic algorithm with corresponding genetic model is developed and integrated into AIRTOBS. As a result, exact and meta-heuristic methods for solving instances of the AMPP complement the existing heuristic method for the AIRMAP. The computational results of a simulation study for the two use cases for aircraft maintenance planning optimization at DLR with the corresponding solving methods are discussed in the course of this thesis. Those results show the practical implications of the presented models and corresponding solving methods and can furthermore be used for future work on task-centric aircraft maintenance planning optimization.