The gate assignment problem (GAP) is an important logistical challenge that managers have to face for the airport operations. Moreover time delays in airport may cause economic losses, thus it becomes of crucial interest to get solutions to problems as soon as possible, and GAP belongs to this category. GAP involves gates and flight, and its aim is to assign each flight to an available gate. Typically this problem has no unique solution. Indeed, this problem consists in allocating flights to gates while considering different objectives. Thus, the solution strongly depends on the considered objectives. This thesis can be divided in two parts. In the first part we illustrate a mathematical formulation to get the optimal solution for our GAP. This problem aims to minimize the total walked distance by transit passengers while keeping the number of apron gates used as minimum as possible. Since this approach is vary time consuming, in the second part of this thesis we introduce a Matheuristic approach, which consists in heuristic optimization method based on the previous mathematical formulation. The latter approach allows to increase time performance in solving flight to gate allocating problem. This leads to an improvement of the airport efficiency.
Il problema di assegnazione dei gate (GAP) è una sfida logistica importante che i man- ager devono affrontare nelle operazioni aeroportuali. Inoltre, i ritardi temporali negli aeroporti possono causare perdite economiche, pertanto diventa di interesse cruciale ottenere soluzioni ai problemi il più presto possibile, e il GAP rientra in questa categoria. Il GAP coinvolge i gate e i voli, e il suo obiettivo è assegnare ogni volo a un gate disponi- bile. Tipicamente, questo problema non ha una soluzione unica. Infatti, questo problema consiste nell’allocare i voli ai gate tenendo conto di diversi obiettivi. Di conseguenza, la soluzione dipende fortemente dagli obiettivi presi in considerazione. Questa tesi può essere divisa in due parti. Nella prima parte illustriamo una formulazione matematica per ottenere la soluzione ottimale per il nostro GAP. Questo problema mira a minimizzare la distanza totale percorsa dai passeggeri in transito, mantenendo il numero di gate di piazzale utilizzati il più basso possibile. Poiché questo approccio richiede molto tempo, nella seconda parte di questa tesi introduciamo un approccio Matheuristico, che consiste in un metodo di ottimizzazione euristico basato sulla precedente formulazione matematica. Quest’ultimo approccio permette di migliorare le prestazioni temporali nella risoluzione del problema di assegnazione dei voli ai gate. Ciò porta a un miglioramento dell’efficienza dell’aeroporto.
A matheuristic approach for the gate assignment problem
Mady, Mohamed
2022/2023
Abstract
The gate assignment problem (GAP) is an important logistical challenge that managers have to face for the airport operations. Moreover time delays in airport may cause economic losses, thus it becomes of crucial interest to get solutions to problems as soon as possible, and GAP belongs to this category. GAP involves gates and flight, and its aim is to assign each flight to an available gate. Typically this problem has no unique solution. Indeed, this problem consists in allocating flights to gates while considering different objectives. Thus, the solution strongly depends on the considered objectives. This thesis can be divided in two parts. In the first part we illustrate a mathematical formulation to get the optimal solution for our GAP. This problem aims to minimize the total walked distance by transit passengers while keeping the number of apron gates used as minimum as possible. Since this approach is vary time consuming, in the second part of this thesis we introduce a Matheuristic approach, which consists in heuristic optimization method based on the previous mathematical formulation. The latter approach allows to increase time performance in solving flight to gate allocating problem. This leads to an improvement of the airport efficiency.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/210653