Optimal aircraft scheduling and routing at a terminal control area during disturbances

Samà, Marcella; D’Ariano, Andrea; D’Ariano, Paolo; Pacciarelli, Dario

doi:10.1016/j.trc.2014.08.005

Cited by 79 publications

(57 citation statements)

References 27 publications

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“…after 180 seconds), implemented in the AGLIBRARY solver. A more detailed description of the alternative graph models, algorithms and solver can be found in D'Ariano et al [5,6] and Samà et al [13][14][15].…”

Section: Terminal Area Aircraft Scheduling Approachmentioning

confidence: 99%

Terminal Control Area Aircraft Scheduling and Trajectory Optimization Approaches

et al. 2017

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Abstract. Aviation authorities are seeking optimization methods to better use the available infrastructure and better manage aircraft movements. This paper deals with the realtime scheduling of take-off and landing aircraft at a busy terminal control area and with the optimization of aircraft trajectories during the landing procedures. The first problem aims to reduce the propagation of delays, while the second problem aims to either minimize the travel time or reduce the fuel consumption. Both problems are particularly complex, since the first one is NP-hard while the second one is nonlinear and a combined solution needs to be computed in a short-time during operations. This paper proposes a framework for the lexicographic optimization of the two problems. Computational experiments are performed for the Milano Malpensa airport and show the existing gaps between the performance indicators of the two problems when different lexicographic optimization approaches are considered.

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Section: Terminal Area Aircraft Scheduling Approachmentioning

confidence: 99%

Terminal Control Area Aircraft Scheduling and Trajectory Optimization Approaches

et al. 2017

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“…We observe that, while the coordination issue is often referred to multi-airport coordination, as in Aktürk et al (2014) or Andreatta et al (2011), this paper focuses on coordination of operations in a single airport. In the latter context, Balakrishnan andChandran (2010), andSölveling et al (2010) focus on the runway scheduling, Artiouchine et al (2008), Hu and Chen (2005), and Di Paolo (2008,2009) focus on the landing scheduling from airspace resources to runways, while other authors deal with the coordination of the TCA airspace and the runways (landing and take-off scheduling), e.g., D'Ariano et al (2012D'Ariano et al ( , 2015, Lieder and Stolletz (2016), Murça and Müller (2015), Samà et al (2013Samà et al ( , 2014Samà et al ( , 2015. Other papers focus on ground control (including taxiway resources and runways), e.g., Atkin et al (2008Atkin et al ( , 2013, Clare andRichards (2011), Marin (2006), Ravizza et al (2013).…”

Section: Introductionmentioning

confidence: 99%

“…Along this stream of research, optimization models tend to incorporate an increasing number of details of the practical problem that affect the feasibility of the solutions. Models in this stream, that we call microscopic optimization models, have been proposed in Bianco et al (2006), D'Ariano et al (2012D'Ariano et al ( , 2015, Samà et al (2013Samà et al ( , 2014Samà et al ( , 2015 for the ASP limited to air resources and runways. Bianco et al (2006) propose a no-wait version of the job shop scheduling problem to model airborne aircraft movements.…”

Section: Introductionmentioning

confidence: 99%

“…D' Ariano et al (2015) include routing and scheduling decisions and solve the problem with a tabu search algorithm. Samà et al (2013Samà et al ( , 2014 develop a Mixed Integer Linear Programming (MILP) formulation to model the problem and develop a rolling horizon approach to solve the ASP without and with aircraft rerouting. However, the latter four works deal with the minimization of maximum delay.…”

Section: Introductionmentioning

confidence: 99%

“…However, the latter four works deal with the minimization of maximum delay. Samà et al (2015 use the same MILP formulation of Samà et al (2013Samà et al ( , 2014 but with different objective functions, including the average delay and average travel time. This paper builds on the former papers with the substantial step forward of incorporating taxiway into the microscopic MILP model.…”

Section: Introductionmentioning

confidence: 99%

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Coordination of scheduling decisions in the management of airport airspace and taxiway operations

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Transportation Research Part A: Policy and Practice

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This paper addresses the real-time problem of coordinating aircraft ground and air operations in an airport area. At a congested airport, airborne decisions are related to take-off and landing operations, while ground (taxiway) decisions consist of scheduling aircraft movements between the gates and the runways. Since the runways are the initial/terminal points of both decisions, coordinated actions have a great potential to improve the overall performance. However, in the traffic control practice the different decisions are taken by different controllers, at least in large airports. Weak coordination may result in long queues at the runways, with increasing aircraft delays and energy consumption. This paper investigates models, methods and policies for improving the coordination between taxiway scheduling and airborne scheduling. The performance of a solution is measured in terms of delay and travel time, the latter being related to the energy consumption of an aircraft. A microscopic mathematical formulation is adopted to achieve reliable solutions. Exact and heuristic methods have been analysed in combination with the different policies, based on practical-size instances from Amsterdam Schiphol airport, in the Netherlands. Computational experience shows that good quality solutions can be found within limited time, compatible with real-time operations.

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Meta-Heuristic Algorithms for Aircraft Sequencing and Scheduling Problem

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Optimal aircraft scheduling and routing at a terminal control area during disturbances

Cited by 79 publications

References 27 publications

Terminal Control Area Aircraft Scheduling and Trajectory Optimization Approaches

Terminal Control Area Aircraft Scheduling and Trajectory Optimization Approaches

Coordination of scheduling decisions in the management of airport airspace and taxiway operations

Meta-Heuristic Algorithms for Aircraft Sequencing and Scheduling Problem

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