Check-in allocation improvements through the use of a simulation–optimization approach

Mota, Miguel Mújica

doi:10.1016/j.tra.2015.04.016

Cited by 25 publications

(11 citation statements)

References 13 publications

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“…DES is an approach that is used in many applications like logistic and manufacturing [17]. Recently DES was also applied to the aviation field with the scope of modelling the airport operation for both airspace and ground, even inside the terminal [19]. Using this approach, it has been possible to make an initial analysis and evaluation of airports performance [20,25,26].…”

Section: Methodsmentioning

confidence: 99%

Improving Airport Performance Through a Model-Based Analysis and Optimization Approach

Mota

Scala

Delahaye

2017

Applied Simulation and Optimization 2

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Traditionally airport systems have been studied using an approach in which the different elements of the system are studied independently. Until recently scientific community has put attention in developing models and techniques that study the system using holistic approaches for understanding cause and effect relationships of the integral system. This chapter presents a case of an airport in which the authors have implemented an approach for improving the turnaround time of the operation. The novelty of the approach is that it uses a combination of simulation, parameter analysis and optimization for getting to the best amount of vehicles that minimize the turnaround time of the airport under study. In addition, the simulation model is such that it includes the most important elements within the aviation system, such as terminal manoeuvring area, runway, taxi networks, and ground handling operation. The results show clearly that the approach is suitable for a complex system in which the amount of variables makes it intractable for getting good solutions in reasonable time.

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Section: Methodsmentioning

confidence: 99%

Improving Airport Performance Through a Model-Based Analysis and Optimization Approach

Mota

Scala

Delahaye

2017

Applied Simulation and Optimization 2

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“…It also mentions the use of computer models as a tool for the evaluation of such systems. In the literature we can find many applications that employ optimization combined with simulation techniques to solve specific airport operations: for instance [20] deals with the problem of reducing the cost of delay in air traffic; [21] focuses on stochastic aircraft recovery problem; [22] considers airport surface traffic; and [23] copes with the check-in allocation at airport terminals. Regarding similar problems as the one faced in this work, in [24] a DES model integrating TMA and airside operations has been developed.…”

Section: Simulation Combined With Optimizationmentioning

confidence: 99%

Tackling Uncertainty for the Development of Efficient Decision Support System in Air Traffic Management

Scala

Mota

et al. 2020

IEEE Trans. Intell. Transport. Syst.

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Airport capacity has become a constraint in the air transportation networks, due to the growth of air traffic demand and the lack of resources able to accommodate this demand. This paper presents the algorithmic implementations of a decision support system for making a more efficient use of the airspace and ground capacity. The system would be able to provide support for air traffic controllers in handling large amount of flights while reducing to a minimum the potential conflicts. In this framework, airspace together with ground airport operations are considered. Conflicts are defined as separation minima violation between aircraft for what concerns airspace and runways, and as capacity overloads for taxiway network and terminals. The methodology proposed in this work consists of an iterative approach that couples optimization and simulation to find solutions that are resilient to perturbations due to the uncertainty present in different phases of the arrival and departure process. An optimization model was employed to find a (sub)optimal solution while a discrete event-based simulation model evaluated the objective function. By coupling simulation with optimization, we generate more robust solutions resilient to variability in the operations, this is supported by a case study of Paris Charles de Gaulle Airport.

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“…The studies previously mentioned reveal that simulation can be a powerful tool for supporting decisions in the planning phase of large and costly infrastructure such as airports. However, its use in the planning phases of an aviation study is not common, although it is an approach that some participants and researchers are actively exploring [13,[16][17][18].…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation-Based Virtual Cycle for Multi-Level Airport Analysis

et al. 2018

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The aeronautical industry is expanding after a period of economic turmoil. For this reason, a growing number of airports are facing capacity problems that can sometimes only be resolved by expanding infrastructure, with the inherent risks that such decisions create. In order to deal with uncertainty at different levels, it is necessary to have relevant tools during an expansion project or during the planning phases of new infrastructure. This article presents a methodology that combines simulation approaches with different description levels that complement each other when applied to the development of a new airport. The methodology is illustrated with an example that uses two models for an expansion project of an airport in The Netherlands. One model focuses on the operation of the airport from a high-level position, while the second focuses on other technical aspects of the operation that challenge the feasibility of the proposed configuration of the apron. The results show that by applying the methodology, analytical power is enhanced and the risk of making the wrong decisions is reduced. We identified the limitations that the future facility will have and the impact of the physical characteristics of the traffic that will operate in the airport. The methodology can be used for tackling different problems and studying particular performance indicators to help decision-makers take more informed decisions.

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Check-in allocation improvements through the use of a simulation–optimization approach

Cited by 25 publications

References 13 publications

Improving Airport Performance Through a Model-Based Analysis and Optimization Approach

Improving Airport Performance Through a Model-Based Analysis and Optimization Approach

Tackling Uncertainty for the Development of Efficient Decision Support System in Air Traffic Management

Simulation-Based Virtual Cycle for Multi-Level Airport Analysis

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