Dynamic scheduling of aircraft landings

Bennell, Julia A.; Mesgarpour, Mohammad; Potts, Chris N.

doi:10.1016/j.ejor.2016.08.015

Cited by 78 publications

(42 citation statements)

References 25 publications

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“…Also, when more operations (departures, runway crossings, etc) are included, the problem is often called the Aircraft Sequencing and Scheduling problem (ASSP). The case in which predicted operations times are known with certainty, called the deterministic case, has been thoroughly studied in the literature [4,7,8], while the case under uncertainty has less often been addressed. So far in the related literature, three main approaches to optimization under uncertainty were applied to ASSP: probabilistic [9,10], stochastic [11][12][13] and robust [14][15][16] approaches.…”

Section: Literature Reviewmentioning

confidence: 99%

Extended Aircraft Arrival Management Under Uncertainty: A Computational Study

Khassiba

Bastin²,

Gendron³

et al. 2019

Journal of Air Transportation

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Arrival Manager operational horizon, in Europe, is foreseen to be extended up to 500 nautical miles around destination airports. In this context, arrivals need to be sequenced and scheduled a few hours before landing, when uncertainty is still significant. A computational study, based on a two-stage stochastic program, is presented and discussed to address the arrival sequencing and scheduling problem under uncertainty. This preliminary study focuses on a single Initial Approach Fix and a single runway. Different problem characteristics, optimization parameters as well as fast solution methods for real-time implementation are analyzed in order to evaluate the viability of our approach. Paris Charles-De-Gaulle airport is taken as a case study. A simulation-based validation experiment shows that our approach can decrease the number of expected conflicts near the terminal area by up to 70%. Moreover, in a high-density traffic situation, the total time-to-lose inside the terminal area can be decreased by more than 71%, while the expected landing rate can be increased by 7.7%, compared to the first-come first-served policy. This computational study demonstrates that sequencing and scheduling arrivals under uncertainty, a few hours before landing, can successfully diminish the need for holding stacks by relying more on upstream linear holding.

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Section: Literature Reviewmentioning

confidence: 99%

Extended Aircraft Arrival Management Under Uncertainty: A Computational Study

Khassiba

Bastin²,

Gendron³

et al. 2019

Journal of Air Transportation

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“…Our research team has also published some relevant papers for the carrier aircraft scheduling problem including the constraints in the scheduling [21], the multi-objective integrated supporting scheduling model, and the intelligence algorithm to solve this problem [22,23]. Compared with other land-based aircraft [24,25], the flight deck in an aircraft carrier presents a complex and uncertain environment in which time-critical scheduling and planning must be done to fulfill mission requirements and ensure the safety of operational crews and equipment [26]. However, most previous research has been aimed at developing better solution methods or scheduling strategies based on a static scheduling environment, and most research is oversimplified.…”

Section: Introductionmentioning

confidence: 99%

A Dynamic Scheduling Method for Carrier Aircraft Support Operation under Uncertain Conditions Based on Rolling Horizon Strategy

Yuan

Wang

et al. 2018

Applied Sciences

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The efficient scheduling of carrier aircraft support operations in the flight deck is important for battle performances. The supporting operations and maintenance processes involve multiple support resources, complex scheduling process, and multiple constraints; the efficient coordination of these processes can be considered a multi-resource constrained multi-project scheduling problem (MRCMPSP), which is a complex non-deterministic polynomial-time hard (NP-hard) problem. The renewable resources include the operational crews, resource stations, and operational spaces, and the non-renewable resources include oil, gas, weapons, and electric power. An integer programming mathematical model is established to solve this problem. A periodic and event-driven rolling horizon (RH) scheduling strategy inspired by the RH optimization method from predictive control technology is presented for the dynamic scheduling environment. The periodic horizon scheduling strategy can track the changes of the carrier aircraft supporting system, and the improved event-driven mechanism can avoid unnecessary scheduling with effective resource allocation under uncertain conditions. The dual population genetic algorithm (DPGA) is designed to solve the large-scale scheduling problem. The activity list encoding method is proposed, and a new adaptive crossover and mutation strategy is designed to improve the global exploration ability. The double schedule for leftward and rightward populations is integrated into the genetic process of alternating iterations to improve the convergence speed and decrease the computation amount. The computational results show that our approach is effective at solving the scheduling problem in the dynamic environment, as well as making better decisions regarding disruption on a real-time basis.

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“…Runway system is the most critical component of airport, especially in major international airports, which is known admitted as the prime reason of delay in the departure/arrival process and contributes to the congestion in the airport terminal area as a result of restricted runway capacity and inefficient operations. The total air transportation demand is growing steadily at a rate between three and five percent in spite of the recent economic recession [1]. Beyond question, the increasing traffic will causes high congestion in the terminal areas due to the limited capacity of runway system that defined as the number of runway operations (i.e., aircraft take-off and landing) in a unit time.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, Lieder et al [10] develop a DP approach combined with a state-space reduction using a dominance criterion, which is able to create optimal landing schedules on multiple independent runways. Bennell et al [1] investigates DP and local search implementation for both static and dynamic ALP. Also, a lot of authors empoy heuristic method as a solution approach (e.g., Bianco et al [11], Beasley et al [12] and Faye [13]).…”

Section: Introductionmentioning

confidence: 99%

A Two-stage Stochastic Programming Approach for Aircraft Landing Problem

Liu

Liang

Zheng

et al. 2018

2018 15th International Conference on Service Systems and Service Management (ICSSSM)

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This paper considers a two-stage stochastic programming problem for airport runway scheduling under the uncertainty of arrival time on a single runway. The goal of airport runway scheduling is to schedule a set of aircrafts in a given time horizon and minimize a corresponding objective while satisfying separation requirements as well as other practical constraints. In order to boost runway elasticity and throughout, a mess of unpredictable factors, such as weather, pilot behavior and airport surface traffic, should be take into consideration by airport regulator. The arrival scheduling problem at airport can be decomposed into sequential decision problem, where the first stage determines the sequence of aircraft weight class, while the individual flight is assigned to positions in the weight class sequence in the second stage. The main mission of this work is to identify an optimal schedule involving the arrival time of flight is stochastic under different scenarios. A stochastic aircraft landing problem (SALP) formulation based on time-dependent traveling salesman problem (TDTSP) is proposed. Then a sample average approximation (SAA) algorithm is developed to solve this stochastic programming and the efficacy is verified by experimental result.

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Dynamic scheduling of aircraft landings

Cited by 78 publications

References 25 publications

Extended Aircraft Arrival Management Under Uncertainty: A Computational Study

Extended Aircraft Arrival Management Under Uncertainty: A Computational Study

A Dynamic Scheduling Method for Carrier Aircraft Support Operation under Uncertain Conditions Based on Rolling Horizon Strategy

A Two-stage Stochastic Programming Approach for Aircraft Landing Problem

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