On air traffic flow management with rerouting. Part I: Deterministic case

Alonso‐Ayuso, Antonio; Escudero, Laureano F.; Pizarro, Celeste

doi:10.1016/j.ejor.2011.12.021

Cited by 60 publications

(47 citation statements)

References 12 publications

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“…Since the development of the optimization problem is largely the same in both [19] and [20], this paper uses the variable notation in the latter. The following sections describe the construction of the decision variables and the constraints.…”

Section: Description Of the Blo Integer Program And Constraint Comentioning

confidence: 99%

“…A key advancement in optimization-based methods for TFM is the Bertsimas/Stock-Patterson (BSP) model [17,18], which poses the TFM problem as a binary integer program (IP). The Bertsimas-Lulli-Odoni (BLO) model [19] and further developments by Agustin et al [20] (the AAEP model) introduce additional flexibility in the BSP model, such as the possibility of multiple routes and fairer distribution of delays among different flights. The BLO and AAEP models formulate the deterministic TFM problem by using a graph abstraction of the airspace with nodes connected by one or more routes for all flights.…”

Section: Introductionmentioning

confidence: 99%

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Optimal Traffic Flow Scheduling Using High-Performance Computing

Sengupta

Kwan

Menon

2015

Journal of Aerospace Information Systems

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Algorithms for the end-to-end optimized scheduling of aircraft to enhance the efficiency of the National Airspace System are developed. For a given set of flights and desired departing schedules, routes are constructed and unimpeded four-dimensional trajectories are simulated. These trajectories serve as an input to a linearprogramming-based approach, and they result in optimized schedules that are deconflicted while assuring adherence to the system capacity constraints. For a large number of flights, the computational effort is formidable and optimization coupled with the Dantzig-Wolfe decomposition technique has been found to be a suitable approach. Techniques for accelerating the decomposition and solver on emerging high-performance computing hardware are discussed. A multithreaded central-processing-unit implementation and a novel implementation on general-purpose graphics processing units show acceleration over a state-of-the-art open-source decomposition-based solver. The acceleration observed can be up to nine times for replicated flights and three times for realistic nationwide traffic flow optimization examples.

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Section: Description Of the Blo Integer Program And Constraint Comentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal Traffic Flow Scheduling Using High-Performance Computing

Sengupta

Kwan

Menon

2015

Journal of Aerospace Information Systems

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“…Strictly, flight routes along an airspace have various configurations and parameters described for each. In the event of air traffic congestion where an alternate flight route is taken, a penalization of the deviation of the total trip length from that scheduled and the deviation of the actual travel time from that scheduled for each flight is charged to the airlines concerned [34]. The same penalization is charged to all airlines regardless of its capital structure and market position, thus demonstrating an equitable treatment of among airlines.…”

Section: (Equitable Treatment Of Competing Airline)mentioning

confidence: 99%

Exploring critical attributes during air traffic congestion with a fuzzy DEMATEL–ANP technique: a case study in Ninoy Aquino International Airport

Bongo

Ocampo

2017

J. Mod. Transport.

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The constant growth of air travel in the Philippines has brought about significant consequences to air traffic congestion. Given limited resources, major airports seek to address this issue while considering various attributes generally affecting air transportation. This paper adopts fuzzy decision-making trial and evaluation laboratory-analytic network process (DEMATEL-ANP) to identify the most critical attributes in the commercial aviation industry. A case study participated by key experts of Ninoy Aquino International Airport was conducted to illustrate the proposed approach. The fuzzy DEMATEL-ANP model performed satisfactorily as it was able to extract the global priority vectors of attributes under a fuzzy environment. The results showed that aviation safety is most prioritized, as can also be seen from the significant influence it brings on other attributes. Following next to safety in terms of priority are attributes that address the general air transportation system such as economic value, environmental value, social value, equitable treatment of competing airline, customer goodwill, and utilization of runway and terminal. Then, attributes relating to passenger cost, fuel cost, extra crew cost, landing/take-off fee, and cost of using flight routes are of last priority. Given the order of priorities and criticality of each attribute, shortterm and long-term policies can be framed accordingly to propose air traffic flow management actions that can best address the issue on congestion.

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“…Dell'Olmo and Lulli [25] developed a two-level hierarchical model including air routes networks and optimal traffic routes using both mixed integer programming and heuristic algorithms. Agusti et al [26,27] developed re-routing approaches for large-scaled deterministic and stochastic ATFM problems.…”

Section: Figurementioning

confidence: 99%

En-Route Airspace Capacity and Traffic Flow Enhancement Using Genetic Algorithms

Çetek¹,

Çeçen²

2017

ANADOLU UNIVERSITY JOURNAL OF SCIENCE AND TECHNOLOGY a - Applied Sciences and Engineering

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Air transportation industry has gone under a rapid and continuous growth for the last four decades. International Civil Aviation Organization (ICAO) and aircraft manufacturers anticipate that annual growth rate of air traffic will be 4.5-5.1% until 2030. Airspace capacity management becomes more critical for the safety, efficiency and sustainable growth of the industry. Enroute areas cover the largest portion of the controlled airspace and are subdivided into small segments referred to as 'en-route sectors'. Each sector is usually monitored and controlled by a single air traffic controller in the relevant Area Control Center (ACC). When air traffic demand reaches or exceeds the available en-route sector capacity, serious aircraft delays occur at airports or in airspace. When air traffic demand reaches to the available en-route sector capacity, serious aircraft delays occur at airports or in airspace. These delays lead not only to system-wide congestions but also interruptions in air traffic services, airline flight schedules and airport operations. Therefore, these interruptions result in increased operational costs, passenger dissatisfaction and air traffic controller workload. This study presents a multiple entry point assignment model based on a genetic algorithm to minimize delays and increase throughput of a generic high-altitude en-route sector. The proposed approach intends to provide a framework for a decision support system based on flexible and dynamic direct route utilization for air traffic and capacity management. The available single entry point sector configuration and its multiple entry point assignment alternatives were compared for various traffic scenarios. Multiple entry point configurations provided up to 10% increase in throughput and significant reductions in average delay per aircraft compared to the single point entry configuration.

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On air traffic flow management with rerouting. Part I: Deterministic case

Cited by 60 publications

References 12 publications

Optimal Traffic Flow Scheduling Using High-Performance Computing

Optimal Traffic Flow Scheduling Using High-Performance Computing

Exploring critical attributes during air traffic congestion with a fuzzy DEMATEL–ANP technique: a case study in Ninoy Aquino International Airport

En-Route Airspace Capacity and Traffic Flow Enhancement Using Genetic Algorithms

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