Abstract
Airport management is frequently faced with a problem
of assigning flights to available stands and parking positions in the
most economical way that would comply with airline policies and
suffer minimum changes due to any operational disruptions. This
work presents a novel approach to the most common airport
problem – efficient stand assignment. The described algorithm
combines benefits of data-mining and metaheuristic approaches
and generates qualitative solutions, aware of delay trends and
airport performance perturbations. The presented work provides
promising solutions from the starting moments of computation, in
addition, it delivers to the airport stakeholders delay-aware stand
assignment, and facilitates the estimation of risk and consequences
of any operational disruptions on the slot adherence.
of assigning flights to available stands and parking positions in the
most economical way that would comply with airline policies and
suffer minimum changes due to any operational disruptions. This
work presents a novel approach to the most common airport
problem – efficient stand assignment. The described algorithm
combines benefits of data-mining and metaheuristic approaches
and generates qualitative solutions, aware of delay trends and
airport performance perturbations. The presented work provides
promising solutions from the starting moments of computation, in
addition, it delivers to the airport stakeholders delay-aware stand
assignment, and facilitates the estimation of risk and consequences
of any operational disruptions on the slot adherence.
| Original language | English |
|---|---|
| Publication status | Published - Dec 2018 |
| Event | SESAR Innovation Days 2018 - the University of Salzburg, Salzburg, Austria Duration: 3 Dec 2018 → 7 Dec 2018 https://www.sesarju.eu/node/3438 |
Conference
| Conference | SESAR Innovation Days 2018 |
|---|---|
| Abbreviated title | SID |
| Country | Austria |
| City | Salzburg |
| Period | 3/12/18 → 7/12/18 |
| Internet address |
