Receding Horizon Control for Aircraft Arrival Sequencing and Scheduling

Hu, Xiao-Bing; Chen, Wen‐Hua

doi:10.1109/tits.2005.848365

Cited by 89 publications

(48 citation statements)

References 17 publications

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“…The main advantages of this method are that the subproblems are easier to solve and require less computational time, moreover, it tackles the problem in a dynamical fashion by updating the decision variables while the window slides along the time horizon, resulting in an improvement of the quality of the solution. This approach has already been employed in similar problems giving good results (Hu and Chen 2005, Zhan, Zhang, Li, Liu, Kwok, Ip, and Kaynak 2010, Furini, Kidd, Persiani, and Toth 2015, Toratani, Ueno, and Higuchi 2015, Man, Delahaye, and Xiao-hao 2015, Ma, Delahaye, Sbihi, and Mongeau 2016. In this approach, each entity (aircraft) is associated with a certain status according to its position relatively to the current window.…”

Section: Optimization Processmentioning

confidence: 97%

A down to earth solution: Applying a robust simulation-optimization approach to resolve aviation problems

Scala¹,

Mujica²,

Delahaye³

2017

2017 Winter Simulation Conference (WSC)

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To cite this version:Paolo Scala, Daniel Delahaye, Miguel Mujica. A down to earth solution: applying a robust simulationoptimization approach to resolve aviation problems. ABSTRACTThis paper deals with the improvement of the robustness of heuristic solutions for aviation systems affected by uncertainty when the resolution of conflicts is implemented. A framework that includes the use of optimization and simulation is described which in turn generates pseudo-optimal schedules. The initial solution is progressively improved by iteratively evaluating the uncertainty in the generated solutions and calibrating in accordance with the objective function. Simulation is used for testing the feasibility of a solution generated by an optimization algorithm in an environment characterized by uncertainty. The results show that the methodology is able to improve solutions for the scenarios with uncertainty, thus making them excellent candidates for being implemented in real environments.

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Section: Optimization Processmentioning

confidence: 97%

A down to earth solution: Applying a robust simulation-optimization approach to resolve aviation problems

Scala¹,

Mujica²,

Delahaye³

2017

2017 Winter Simulation Conference (WSC)

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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%

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

Samà

D’Ariano

Corman

et al. 2018

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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“…One common approach adopted by works on solving the dynamic ASS is the use of a rolling horizon window, such as the study of the receding horizon control (RHC) (Hu and Chen 2005a) method and its extended works (Hu and Chen 2005b;Hu and Di 2008;Zhan et al 2010). The RHC methods divide a dynamic ASS problem into a number of static subproblems based on a sliding time window (Hu and Chen 2005a).…”

Section: Introductionmentioning

confidence: 99%

An evolutionary approach for dynamic single-runway arrival sequencing and scheduling problem

Cao

Wei

et al. 2016

Soft Comput

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Aircraft arrival sequencing and scheduling is a classic problem in the air traffic control to ensure safety and order of the operations at the terminal area. Most of the related studies have formulated this problem as a static case and assume the information of all the flights is known in advance. However, the operation of the terminal area is actually a dynamic incremental process. Various kinds of uncertainties may exist during this process, which will make the scheduling decision obtained in the static environment inappropriate. In this paper, aircraft arrival sequencing and scheduling problem is tackled in the form of a dynamic optimization problem. An evolutionary approach, namely dynamic sequence searching and evaluation, is proposed. The proposed approach employs an estimation of distribution algorithm and a heuristic search method to seek the optimal landing sequence of flights. Compared with other related algorithms, the proposed method performs much better on several test instances including an instance obtained from the real data of the Beijing Capital International Airport.

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Receding Horizon Control for Aircraft Arrival Sequencing and Scheduling

Cited by 89 publications

References 17 publications

A down to earth solution: Applying a robust simulation-optimization approach to resolve aviation problems

A down to earth solution: Applying a robust simulation-optimization approach to resolve aviation problems

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

An evolutionary approach for dynamic single-runway arrival sequencing and scheduling problem

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