| Author: | He, Yonghuan |
| Title: | Mitigating aircraft maintenance uncertainties in aircraft routing problems |
| Advisors: | Chung, S. H. Nick (ISE) Chan, T. S. Felix (ISE) |
| Degree: | Ph.D. |
| Year: | 2023 |
| Subject: | Airlines -- Management Airplanes -- Maintenance and repair Hong Kong Polytechnic University -- Dissertations |
| Department: | Department of Industrial and Systems Engineering |
| Pages: | xii, 127 pages : color illustrations |
| Language: | English |
| Abstract: | Airlines are faced with challenging situations, i.e., narrow profit margins and stochastic environments. Consequently, airlines struggle for operational cost reduction and robust schedules to enhance their profitability and competitiveness. The maintenance cost, due to its significance and expensive nature, has drawn increasing attention. The aircraft maintenance routing problem thus becomes increasingly important for airlines. Hence, this research study focuses on enhancing decision making in aircraft schedules from two aspects, with a view to improve cost-efficiency and robustness. From the perspective of cost-efficiency enhancement, it can be observed that there is an increasing willingness for airlines to contract-out their aircraft maintenance services, resulting in procurement circumstances in which maintenance providers offer quantity discounts to airlines. However, most of the models in the literature have ignored such advantageous policies. This motivates us to construct a new model, with a piecewise cost function for exploiting the total quantity discount policy. In solving the proposed model, we develop a column generation- based diving heuristic approach, which proves its effectiveness and efficiency through computational experiments. In addition, the computational results also reveal that the new model enables a noteworthy cost reduction compared with the traditional models. From the perspective of robustness enhancement, this study first concentrates on constructing robust aircraft routes with flexibility. The aircraft maintenance outsourcing creates a new way for airlines to modify the maintenance arrangements. This motivates us to investigate the potential effects of the maintenance distribution structure on the robustness of aircraft routings. Based on this exploration, a robustness strategy encouraging swapping possibilities is additionally integrated into the aircraft maintenance routing problem. Accordingly, a new robust model is proposed. Our computational results demonstrate that a more concentrated maintenance can create more swapping possibilities for aircraft routes. Furthermore, the results also suggest that the routing solutions resulting from our proposed model enable a further improvement in robustness. On the other hand, attempts are also made in constructing robust aircraft routes with improved stability. It is acknowledged that a critical challenge in aircraft routings is the stochasticity of maintenance execution, while most of the traditional models of the aircraft maintenance routing considered the sources of disruptions in an aggregated manner. Therefore, we incorporate the uncertainties of heterogenous maintenance tasks into the robust aircraft routing decision framework, while considering other sources of disruptions. Accordingly, a new robust model is constructed, along with a tailored column generation approach. We analyze the impact of distinct degrees of maintenance uncertainties on the robustness of aircraft routes through computational experiments. In conclusion, the desire for cost and disruption management by airlines motivates the research work conducted in this thesis. Firstly, a new aircraft maintenance routing model integrating the total quantity discount is proposed. Secondly, the effect of the maintenance distribution structure on route robustness is investigated, and a novel robust model considering both the total quantity discount and a robustness strategy encouraging swapping possibilities is constructed. Thirdly, a new robust aircraft maintenance routing model incorporating the maintenance uncertainties of heterogenous maintenance tasks is developed. |
| Rights: | All rights reserved |
| Access: | open access |
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