Using submodularity within column generation to solve the flight-to-gate assignment problem

•Trackable column generation method for large-sized flight-to-gate assignment problems.•Use of submodularity in column generation in solving pricing problems.•Combination of exact algorithms and approximation algorithms in solving pricing problems. In this paper, we provide a column generation-based...

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Veröffentlicht in:Transportation research. Part C, Emerging technologies Jg. 129; S. 103217
Hauptverfasser: Li, Yijiang, Clarke, John-Paul, Dey, Santanu S.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.08.2021
Schlagworte:
Approximation algorithms
Column generation
Dynamic programming
Flight-to-gate assignment
Submodularity
Flight-to-gate assignment
Approximation algorithms
Column generation
Submodularity
Dynamic programming
ISSN:0968-090X, 1879-2359
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Zusammenfassung:•Trackable column generation method for large-sized flight-to-gate assignment problems.•Use of submodularity in column generation in solving pricing problems.•Combination of exact algorithms and approximation algorithms in solving pricing problems. In this paper, we provide a column generation-based approach for solving the airport flight-to-gate assignment problem, where the goal is to minimize the on-ground portion of arrival delays by optimally assigning each scheduled flight to a compatible gate. Specifically, we use a set covering formulation for the master problem and decompose the pricing problem such that each gate is the basis for an independent pricing problem to be solved for assignment patterns with negative reduced costs. We use a combination of an approximation algorithm based on the submodularity of the underlying set and dynamic programming algorithms to solve the independent pricing problems. To the best of our knowledge, this is the first use of submodularity property to efficiently solve pricing problems and improve the performance of column generation algorithm. We show that the dynamic programming algorithm is pseudo-polynomial when there are integer inputs. We also design and employ a rolling horizon method and block decomposition algorithm to solve large-sized instances. Finally, we perform extensive computational experiments to validate the performance of our approach.
ISSN:0968-090X
1879-2359
DOI:10.1016/j.trc.2021.103217