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Paolo Scala
Amsterdam School of International Business, Amsterdam University of Applied Sciences

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Journal article
Published: 14 July 2021 in Case Studies on Transport Policy
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With the increase of needs for controlling the passengers that use different modes of transport such as airports, ports, trains, or future ones as hyper loops, security facilities are a key element to be optimized. In the current study we present an analysis of a security area within an airport with particular restrictions. To improve the capacity, different categories and policies were devised for processing passengers and we propose to adapt the system to these categories and policies. The results indicated that, by designing a proper category in combination with novel technology, it is possible to increase the capacity to values of 2 digits (in terms of passengers/day). As a proof-of-concept, we use a case study of an area within an airport in Mexico based on data and layout of early 2019.

ACS Style

Miguel Mujica Mota; Paolo Scala; Alejandro Murrieta-Mendoza; Angel Orozco; Alejandro Di Bernardi. Analysis of security lines policies for improving capacity in airports: case mexico city. Case Studies on Transport Policy 2021, 1 .

AMA Style

Miguel Mujica Mota, Paolo Scala, Alejandro Murrieta-Mendoza, Angel Orozco, Alejandro Di Bernardi. Analysis of security lines policies for improving capacity in airports: case mexico city. Case Studies on Transport Policy. 2021; ():1.

Chicago/Turabian Style

Miguel Mujica Mota; Paolo Scala; Alejandro Murrieta-Mendoza; Angel Orozco; Alejandro Di Bernardi. 2021. "Analysis of security lines policies for improving capacity in airports: case mexico city." Case Studies on Transport Policy , no. : 1.

Journal article
Published: 29 May 2021 in Aerospace
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Paris Charles de Gaulle Airport was the second European airport in terms of traffic in 2019, having transported 76.2 million passengers. Its large infrastructures include four runways, a large taxiway network, and 298 aircraft parking stands (131 contact) among three terminals. With the current pandemic in place, the European air traffic network has declined by −65% flights when compared with 2019 traffic (pre-COVID-19), having a severe negative impact on the aviation industry. More and more often taxiways and runways are used as parking spaces for aircraft as consequence of the drastic decrease in air traffic. Furthermore, due to safety reasons, passenger terminals at many airports have been partially closed. In this work we want to study the effect of the reduction in the physical facilities at airports on airspace and airport capacity, especially in the Terminal Manoeuvring Area (TMA) airspace, and in the airport ground side. We have developed a methodology that considers rare events such as the current pandemic, and evaluates reduced access to airport facilities, considers air traffic management restrictions and evaluates the capacity of airport ground side and airspace. We built scenarios based on real public information on the current use of the airport facilities of Paris Charles de Gaulle Airport and conducted different experiments based on current and hypothetical traffic recovery scenarios. An already known optimization metaheuristic was implemented for optimizing the traffic with the aim of avoiding airspace conflicts and avoiding capacity overloads on the ground side. The results show that the main bottleneck of the system is the terminal capacity, as it starts to become congested even at low traffic (35% of 2019 traffic). When the traffic starts to increase, a ground delay strategy is effective for mitigating airspace conflicts; however, it reveals the need for additional runways.

ACS Style

Paolo Scala; Miguel Mujica Mota; Daniel Delahaye. Air Traffic Management during Rare Events Such as a Pandemic: Paris Charles de Gaulle Case Study. Aerospace 2021, 8, 155 .

AMA Style

Paolo Scala, Miguel Mujica Mota, Daniel Delahaye. Air Traffic Management during Rare Events Such as a Pandemic: Paris Charles de Gaulle Case Study. Aerospace. 2021; 8 (6):155.

Chicago/Turabian Style

Paolo Scala; Miguel Mujica Mota; Daniel Delahaye. 2021. "Air Traffic Management during Rare Events Such as a Pandemic: Paris Charles de Gaulle Case Study." Aerospace 8, no. 6: 155.

Journal article
Published: 28 December 2020 in Transportation Research Part C: Emerging Technologies
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This paper presents an innovative approach that combines optimization and simulation techniques for solving scheduling problems under uncertainty. We introduce an Opt–Sim closed-loop feedback framework (Opt–Sim) based on a sliding-window method, where a simulation model is used for evaluating the optimized solution with inherent uncertainties for scheduling activities. The specific problem tackled in this paper, refers to the airport capacity management under uncertainty, and the Opt–Sim framework is applied to a real case study (Paris Charles de Gaulle Airport, France). Different implementations of the Opt–Sim framework were tested based on: parameters for driving the Opt–Sim algorithmic framework and parameters for driving the optimization search algorithm. Results show that, by applying the Opt–Sim framework, potential aircraft conflicts could be reduced up to 57% over the non-optimized scenario. The proposed optimization framework is general enough so that different optimization resolution methods and simulation paradigms can be implemented for solving scheduling problems in several other fields.

ACS Style

Paolo Scala; Miguel Mujica Mota; Cheng-Lung Wu; Daniel Delahaye. An optimization–simulation closed-loop feedback framework for modeling the airport capacity management problem under uncertainty. Transportation Research Part C: Emerging Technologies 2020, 124, 102937 .

AMA Style

Paolo Scala, Miguel Mujica Mota, Cheng-Lung Wu, Daniel Delahaye. An optimization–simulation closed-loop feedback framework for modeling the airport capacity management problem under uncertainty. Transportation Research Part C: Emerging Technologies. 2020; 124 ():102937.

Chicago/Turabian Style

Paolo Scala; Miguel Mujica Mota; Cheng-Lung Wu; Daniel Delahaye. 2020. "An optimization–simulation closed-loop feedback framework for modeling the airport capacity management problem under uncertainty." Transportation Research Part C: Emerging Technologies 124, no. : 102937.

Journal article
Published: 04 July 2019 in IEEE Transactions on Intelligent Transportation Systems
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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 potential conflicts. In this framework, airspace together with ground airport operations is considered. The 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 paper 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, and this is supported by a case study of Paris Charles de Gaulle Airport.

ACS Style

Paolo Scala; Miguel Mujica Mota; Ji Ma; Daniel Delahaye. Tackling Uncertainty for the Development of Efficient Decision Support System in Air Traffic Management. IEEE Transactions on Intelligent Transportation Systems 2019, 21, 3233 -3246.

AMA Style

Paolo Scala, Miguel Mujica Mota, Ji Ma, Daniel Delahaye. Tackling Uncertainty for the Development of Efficient Decision Support System in Air Traffic Management. IEEE Transactions on Intelligent Transportation Systems. 2019; 21 (8):3233-3246.

Chicago/Turabian Style

Paolo Scala; Miguel Mujica Mota; Ji Ma; Daniel Delahaye. 2019. "Tackling Uncertainty for the Development of Efficient Decision Support System in Air Traffic Management." IEEE Transactions on Intelligent Transportation Systems 21, no. 8: 3233-3246.

Conference paper
Published: 01 January 2019 in THE EUROPEAN MODELING AND SIMULATION SYMPOSIUM
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This study presents a model-based analysis of the ground connectivity performance of the future Santa Lucia-Mexico City multi-airport system. The plan of the current government is to connect the two airports by a dedicated line, either by bus or other transport so that passengers and airlines can get the benefit of a coordinated operation. Performance indicators such as minimum connecting time, vehicle utilization and passenger waiting time are used to evaluate the future performance. Results reveal that when all passengers are allowed to use the connection, a big number of vehicles are required for providing a good level of service while in the case of a restricted use to only transfer passengers the operation with Bus would have a good performance.

ACS Style

Miguel Mujica Mota; Paolo Scala; Danny Spit; Reyhan Tasdelen. Modelling of the ground connection between two airports in a multi-airport system: case Santa Lucia - Mexico City. THE EUROPEAN MODELING AND SIMULATION SYMPOSIUM 2019, 375 -383.

AMA Style

Miguel Mujica Mota, Paolo Scala, Danny Spit, Reyhan Tasdelen. Modelling of the ground connection between two airports in a multi-airport system: case Santa Lucia - Mexico City. THE EUROPEAN MODELING AND SIMULATION SYMPOSIUM. 2019; ():375-383.

Chicago/Turabian Style

Miguel Mujica Mota; Paolo Scala; Danny Spit; Reyhan Tasdelen. 2019. "Modelling of the ground connection between two airports in a multi-airport system: case Santa Lucia - Mexico City." THE EUROPEAN MODELING AND SIMULATION SYMPOSIUM , no. : 375-383.

Journal article
Published: 19 December 2018 in Transportation Research Part C: Emerging Technologies
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Airports and surrounding airspaces are limited in terms of capacity and represent the major bottlenecks of the air traffic management system. This paper addresses the problems of terminal airspace management and airport congestion management at the macroscopic level through the integrated control of arrivals and departures. Conflict detection and resolution methods are applied to a predefined terminal route structure. Different airside components are modeled using network abstraction. Speed, arrival and departure times, and runway assignment are managed by using an optimization method. An adapted simulated annealing heuristic combined with a time decomposition approach is proposed to solve the corresponding problem. Computational experiments performed on case studies of Paris Charles De-Gaulle airport show some potential improvements: First, when the airport capacity is decreased, until a certain threshold, the overload can be mitigated properly by adjusting the aircraft entry time in the Terminal Maneuvering Area and the pushback time. Second, landing and take-off runway assignments in peak hours with imbalanced runway throughputs can significantly reduce flight delays. A decrease of 37% arrival delays and 36% departure delays was reached compared to baseline case.

ACS Style

Ji Ma; Daniel Delahaye; Mohammed Sbihi; Paolo Scala; Miguel Antonio Mujica Mota. Integrated optimization of terminal maneuvering area and airport at the macroscopic level. Transportation Research Part C: Emerging Technologies 2018, 98, 338 -357.

AMA Style

Ji Ma, Daniel Delahaye, Mohammed Sbihi, Paolo Scala, Miguel Antonio Mujica Mota. Integrated optimization of terminal maneuvering area and airport at the macroscopic level. Transportation Research Part C: Emerging Technologies. 2018; 98 ():338-357.

Chicago/Turabian Style

Ji Ma; Daniel Delahaye; Mohammed Sbihi; Paolo Scala; Miguel Antonio Mujica Mota. 2018. "Integrated optimization of terminal maneuvering area and airport at the macroscopic level." Transportation Research Part C: Emerging Technologies 98, no. : 338-357.

Conference paper
Published: 19 December 2018 in Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016
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ACS Style

Paolo Scala; Miguel Mujica Mota; Daniel Delahaye. Implementation of an Optimization and Simulation-Based Approach for Detecting and Resolving Conflicts at Airports. Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016 2018, 258 -264.

AMA Style

Paolo Scala, Miguel Mujica Mota, Daniel Delahaye. Implementation of an Optimization and Simulation-Based Approach for Detecting and Resolving Conflicts at Airports. Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016. 2018; (142):258-264.

Chicago/Turabian Style

Paolo Scala; Miguel Mujica Mota; Daniel Delahaye. 2018. "Implementation of an Optimization and Simulation-Based Approach for Detecting and Resolving Conflicts at Airports." Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM 2016, The 57th SIMS Conference on Simulation and Modelling SIMS 2016 , no. 142: 258-264.

Journal article
Published: 19 April 2018 in Aerospace
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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.

ACS Style

Miguel Mujica Mota; Alejandro Di Bernardi; Paolo Scala; Gabriel Ramirez-Diaz. Simulation-Based Virtual Cycle for Multi-Level Airport Analysis. Aerospace 2018, 5, 44 .

AMA Style

Miguel Mujica Mota, Alejandro Di Bernardi, Paolo Scala, Gabriel Ramirez-Diaz. Simulation-Based Virtual Cycle for Multi-Level Airport Analysis. Aerospace. 2018; 5 (2):44.

Chicago/Turabian Style

Miguel Mujica Mota; Alejandro Di Bernardi; Paolo Scala; Gabriel Ramirez-Diaz. 2018. "Simulation-Based Virtual Cycle for Multi-Level Airport Analysis." Aerospace 5, no. 2: 44.

Conference paper
Published: 01 December 2017 in 2017 Winter Simulation Conference (WSC)
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This 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.

ACS Style

Paolo Scala; Miguel Mujica; Daniel Delahaye. A down to earth solution: Applying a robust simulation-optimization approach to resolve aviation problems. 2017 Winter Simulation Conference (WSC) 2017, 2626 -2637.

AMA Style

Paolo Scala, Miguel Mujica, Daniel Delahaye. A down to earth solution: Applying a robust simulation-optimization approach to resolve aviation problems. 2017 Winter Simulation Conference (WSC). 2017; ():2626-2637.

Chicago/Turabian Style

Paolo Scala; Miguel Mujica; Daniel Delahaye. 2017. "A down to earth solution: Applying a robust simulation-optimization approach to resolve aviation problems." 2017 Winter Simulation Conference (WSC) , no. : 2626-2637.