Stochastic terminal flight arrival and departure scheduling problem under performance-based navigation environment

Yang, Yuanchao; Gao, Zichen; He, Chao

doi:10.1016/j.trc.2020.102735

Cited by 13 publications

(8 citation statements)

References 30 publications

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“…For further references, let's look at the most relevant airport and airline operations and scheduling problems. Readers may refer to the following literature for air traffic management (Jungai and Hongjun 2012), (Takeichi 2017), (Çiftçi and Özkır 2020), (Mondoloni and Rozen 2020), and (Sáez et al 2020), for arrival/departure scheduling (Rathinam et al 2009), (Ng et al 2017), and(Yang et al 2020), for ground operations (Alomar and Tolujevs 2017), and (Xiao et al 2020), for hub and spoke network planning (Sedehzadeh et al 2016), (Bao and Hua 2017), and, (Fan et al 2018).…”

Section: Literature Surveymentioning

confidence: 99%

“…When we reviewed the literature, flight scheduling problems, fleet assignment, aircraft routing, crew scheduling, workforce planning, revenue management, fuel management, airline irregular operations, gate assignment, aircraft boarding strategy, hub and spoke network planning, demand planning, maintenance planning, onboard catering, arrival scheduling, departure scheduling, runway scheduling are commonly studied airport and airline operations and scheduling problems. Although flight scheduling, arrival scheduling, departure scheduling, and hub and spoke network optimization have been widely studied in the literature, the problem of arrival and departure synchronization and optimization has not been addressed as in this study (Pita et al 2013), (Rathinam et al 2009), (Bazargan 2010), (Dong et al 2016), (Sedehzadeh et al 2016), (Bao and Hua 2017), (Ng et al 2017), (Fan et al 2018), (Kenan et al 2018), and (Yang et al 2020).…”

Section: Introductionmentioning

confidence: 99%

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Synchronization and Optimization of Arrival and Departure Flights in Hub Airports and Airline Companies

Demir

Derviş

2022

Preprint

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With an annual passenger capacity of more than 4 billion and a rapidly increasing number, air transport is the undisputed leader among other travel options for long-distance traveling. There are unique airline connections between more than 20 thousand cities in the world. Despite this, many passengers fly via connecting as there are no direct flights from many cities to many cities or because direct flights are sometimes not economical or common. Since passengers do not like to wait in transfers, passengers are lost to other flights and airline companies if the airline does not have a suitable flight at the appropriate time for the transfer. Arrival and departure synchronization is vital at major hub airports and major airlines. In this study, the synchronization of arrival and departure flights is solved for Istanbul airport, an important hub airport worldwide, using data from a prominent airline company. Three metaheuristic methods, Evolutionary Strategies (ES), Modified Discrete Particle Swarm Optimization (MDPSO), and Random Search (RS) were used, and the results were compared with the original plan (OP). ES and MDPSO were found to be promising solution methods, and they provided substantially increased acquired passengers during connecting flights.

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Section: Literature Surveymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Synchronization and Optimization of Arrival and Departure Flights in Hub Airports and Airline Companies

Demir

Derviş

2022

Preprint

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“…Scholars on the issue of runway sequencing for approach and departure flights have carried out some preliminary research. The research on the ARSP model has gradually matured [1], whose theory research tends to be complicated [2], and the number of model constraints are increasing [3]. The complex ARSP model places greater demands on the algorithm's efficiency, and many scientific papers have described improvements in the efficiency of ARSP-solving algorithms.…”

Section: Introductionmentioning

confidence: 99%

Estimation Distributed Algorithm to Aid Aircraft Runway Scheduling Problem

Liu

2023

J. Phys.: Conf. Ser.

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In this paper, we proposed a runway sequencing and optimal scheduling method. This includes constructing a flight sequencing model to minimize design delay time for arrival and departure flights and designing flight sequencing rules to obtain large-scale feasible runway usage sequences efficiently. Furthermore, a Kendall-τ distance-based Mallows model is constructed based on the obtained flight sequences. An Estimation Distributed Algorithm (EDA) is used to assign each flight a runway usage time that meets the constraint so that the total delay time is minimized. Finally, it is verified that the method can not only reduce the total delay time of the flight as a whole but also has significant performance and is highly implementable through the analysis of calculation cases.

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“…Moreover, the proposed benefits of RNAV include smoother trajectories, reduction in fuel consumption, potential reduction in ATC workload [31][32][33], and the satisfaction of PBN requirements [34]. Waypoints play an important role in the facilitation of smooth trajectories and flexibility in transit in RNAV.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Analysis of Terminal Area Navigation and Conventional Standard Arrival Routes with Cellular Automata

Ogedengbe

Wong

Liem

2023

AIAA AVIATION 2023 Forum

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Aircraft arrival at airports is limited by the physical configuration and layout of the terminal maneuvering area (TMA), which might result in a bottleneck. In a bottleneck situation, navigation is made difficult because arriving aircraft will need special considerations to manage congestion and guarantee safety. In addition, the operating cost of airline operators increases with higher fuel consumption encountered in the extra airborne time. Likewise, passengers incur more travel time with the additional arrival delays. Traditional arrival adopts conventional standard arrival route (STAR), with trajectories that are rigidly coordinated by air traffic controller (ATC). However, a more flexible approach to general navigation has also been introduced, namely the area navigation (RNAV), which makes provision for flexibility in aircraft path selection. This flexibility is enabled by abstract navigational elements, namely waypoints that are unlike conventional navigational aids (NAVAIDs). We look at a modeling framework that juxtaposes the key elements of the traditional STAR (procedure-based) navigation and RNAV (performance-based) navigation. We adopt the cellular automata (CA) framework that has the capability to model the dynamic interaction between aircraft, inherent environmental uncertainties, and arrival route as defined by waypoints. To this end, we develop a modeling environment that enables a fair comparison between these two approaches under similar conditions to determine their respective viability. The effect of the number of waypoints in the TMA under different traffic conditions is illustrated using the relationship between TMA occupancy, traffic flow, and the landing rate. Results show that RNAV navigation exhibits more sensitivity to waypoint distribution within the TMA in terms of throughput, compared to STAR navigation. STAR navigation, on the other hand, demonstrates inherent latency that allows for higher capacities, albeit at the risk of initiating abrupt jamming when a high number of waypoints are active. Consequently, we are able to establish guidelines that justify the adoption RNAV over STAR and vice versa. Furthermore, we also identify performance disparities between them, and where each approach is desirable.

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Stochastic terminal flight arrival and departure scheduling problem under performance-based navigation environment

Cited by 13 publications

References 30 publications

Synchronization and Optimization of Arrival and Departure Flights in Hub Airports and Airline Companies

Synchronization and Optimization of Arrival and Departure Flights in Hub Airports and Airline Companies

Estimation Distributed Algorithm to Aid Aircraft Runway Scheduling Problem

A Comparative Analysis of Terminal Area Navigation and Conventional Standard Arrival Routes with Cellular Automata

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