An improved column generation algorithm for the disrupted flight recovery problem with discrete flight duration control and aircraft assignment constraints
•A new implementation for changing flight duration as a recovery option.•Considering aircraft assignment constraints in the flight recovery problem.•An improved column generation algorithm for larger-scale problems.•Validate algorithm efficiency and provide managerial insights. The disrupted flight...
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Veröffentlicht in: | Computers & industrial engineering 2022-12, Vol.174, p.108772, Article 108772 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •A new implementation for changing flight duration as a recovery option.•Considering aircraft assignment constraints in the flight recovery problem.•An improved column generation algorithm for larger-scale problems.•Validate algorithm efficiency and provide managerial insights.
The disrupted flight recovery problem is well-studied in the literature owing to its significant impact on airlines and passengers. In this work, we consider the disrupted flight recovery problem with two new realistic aspects, i.e., a new implementation for changing flight duration as a recovery option and considering the aircraft assignment constraints. Firstly, we develop a new mixed-integer quadratic programming model encapsulating a functional relationship between the reduced flight duration and the changes in fuel consumption using a piecewise function. Secondly, we propose an improved column generation approach to solve some scenarios based on actual flight data obtained from an airline. Lastly, the experimental results show that the improved column generation algorithm can obtain the optimal solution for all scenarios. Compared with not considering changing the flight duration, considering changing the flight duration can save about 24% of recovery costs on average. In addition, we analyze the effect of enforcing aircraft assignment constraints and different fuel prices on recovery costs. Based on the experimental results, we discuss how to support practitioners in choosing the appropriate combination of recovery options. |
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ISSN: | 0360-8352 1879-0550 |
DOI: | 10.1016/j.cie.2022.108772 |