Assigning airport ground handling operations: a data‐driven matheuristic

Abstract In this paper, we study a problem in the crossover between vehicle routing and scheduling problems. The multi‐trip capacitated vehicle routing and scheduling problem with time windows and meal breaks is extended to a heterogeneous fleet of trucks and drivers, with qualifications and different loading patterns. We propose an optimisation model that solves the problem in reasonable time for small instances. Then, we introduce two heuristics in order to deal with real‐life cases: a greedy heuristic and a matheuristic extension, the latter building upon exact methods to solve parts of the problem. We tested our algorithms on multiple new real‐life instances on U.S. airports. Our computational study compares the effectiveness of each approach and asserts the strength of our matheuristic. Moreover, we implemented our algorithms to help ground handlers specialised in catering operations to speed up the decision‐making process of assigning hundreds of tasks every day, with conclusive results.

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Publication Details

Journal
International Transactions in Operational Research
Published
2025-05-19
DOI
https://doi.org/10.1111/itor.70034
Citations
1
Primary Topic
Vehicle Routing Optimization Methods
Type
article
Field-Weighted Citation Impact
1.24

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article

Assigning airport ground handling operations: a data‐driven matheuristic

Ronan Guivarch, Vincent Charvillat, Daniel Ruíz, Sandrine Mouysset et al.
1 citations
International Transactions in Operational Research
Vehicle Routing Optimization Methods
1.24
article

Assigning airport ground handling operations: a data‐driven matheuristic

Ronan Guivarch, Vincent Charvillat, Daniel Ruíz, Sandrine Mouysset, Alexandre Dupaquis, Frédéric Bouilhaguet
article en
1 citations

Abstract

Abstract In this paper, we study a problem in the crossover between vehicle routing and scheduling problems. The multi‐trip capacitated vehicle routing and scheduling problem with time windows and meal breaks is extended to a heterogeneous fleet of trucks and drivers, with qualifications and different loading patterns. We propose an optimisation model that solves the problem in reasonable time for small instances. Then, we introduce two heuristics in order to deal with real‐life cases: a greedy heuristic and a matheuristic extension, the latter building upon exact methods to solve parts of the problem. We tested our algorithms on multiple new real‐life instances on U.S. airports. Our computational study compares the effectiveness of each approach and asserts the strength of our matheuristic. Moreover, we implemented our algorithms to help ground handlers specialised in catering operations to speed up the decision‐making process of assigning hundreds of tasks every day, with conclusive results.

International Transactions in Operational ResearchVol. 33(1)
Université Toulouse III - Paul Sabatier (FR), Université Fédérale de Toulouse Midi-Pyrénées (FR), Institut Mines-Télécom (FR), Université Toulouse-I-Capitole (FR), Institut de Recherche en Informatique de Toulouse (FR), Université Toulouse - Jean Jaurès (FR), Institut Polytechnique de Bordeaux (FR)
Association Nationale de la Recherche et de la Technologie
Openalex Percentile: Top 19%
Vehicle Routing Optimization Methods
1.24
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