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Opt-Sim approach for the gate allocation problem in covid-19 times

This study tackles the gate allocation problem (GAP) at the airport terminal, considering the current covid-19 pandemic restrictions. The GAP has been extensively studied by the research community in the last decades, as it represents a critical factor that determines an airport's capacity. Currently, the airport passenger terminal operations have been redesigned to be aligned and respect the covid-19 regulation worldwide. This provides operators with new challenges on how to handle the passengers inside the terminal. The purpose of this study is to come up with an efficient gate allocator that considers potential issues derived by the current pandemic, i.e., avoid overcrowded areas. A sim-opt approach has been developed where an evolutionary algorithm (EA) is used in combination with a dynamic passenger flow simulation model to find a feasible solution. The EA aims to find a (sub)optimal solution for the GAP, while the simulation model evaluates its efficiency and feasibility in a real-life scenario. To evaluate the potential of the Opt-Sim approach, it has been applied to a real airport case study.

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Opt-Sim approach for the gate allocation problem in covid-19 times

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An optimization-simulation closed-loop feedback framework for modeling the airport capacity management problem under uncertainty

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 riving 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.

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An optimization-simulation closed-loop feedback framework for modeling the airport capacity management problem under uncertainty

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SIM-OPT in the Loop: Algorithmic Framework for Solving Airport Capacity Problems

The following paper presents an innovative approach for dealing with complex capacity problems in aviation. We introduce a sliding window framework composed by an optimization method with a simulation component. By applying this framework in diverse problems that are dependent on time it is possible to find feasible and close-to-reality solutions in shorter time than the ones that could be achieved by evaluating the problem in the complete time-horizon. The framework can be applied to solve diverse problems in aviation or similar industries. We exemplify the approach with a model of Paris Charles de Gaulle Airport in France.

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Optimization-Simulation implementations for harmonizing operations at big airports

The constant growth of air traffic, especially in Europe, is putting pressure on airports, which, in turn, are suffering congestion problems. The airspace surrounding airport, terminal manoeuvring area (TMA), is particularly congested, since it accommodates all the converging traffic to and from airports. Besides airspace, airport ground capacity is also facing congestion problems, as the inefficiencies coming from airspace operations are transferred to airport ground and vice versa. The main consequences of congestion at airport airspace and ground, is given by the amount of delay generated, which is, in turn, transferred to other airports within the network. Congestion problems affect also the workload of air traffic controllers that need to handle this big amount of traffic.This thesis deals with the optimization of the integrated airport operations, considering the airport from a holistic point of view, by including operations such as airspace and ground together. Unlike other studies in this field of research, this thesis contributes by supporting the decisions of air traffic controllers regarding aircraft sequencing and by mitigating congestion on the airport ground area. The airport ground operations and airspace operations can be tackled with two different levels of abstractions, macroscopic or microscopic, based on the time-frame for decision-making purposes. In this thesis, the airport operations are modeled at a macroscopic level.The problem is formulated as an optimization model by identifying an objective function that considers the amount of conflicts in the airspace and capacity overload on the airport ground; constraints given by regulations on separation minima between consecutive aircraft in the airspace and on the runway; decision variables related to aircraft entry time and entry speed in the airspace, landing runway and departing runway choice and pushback time. The optimization model is solved by implementing a sliding window approach and an adapted version of the metaheuristic simulated annealing. Uncertainty is included in the operations by developing a simulation model and by including stochastic variables that represent the most significant sources of uncertainty when considering operations at a macroscopic level, such as deviation from the entry time in the airspace, deviation in the average taxi time and deviation in the pushback time. In this thesis, optimization and simulation techniques are combined together by developing two methods that aim at improving the solution robustness and feasibility. The first method acts as a validation tool for the optimized solution, and it improves the robustness of solution by iteratively fine-tuning some of the optimization model input parameters. The second method embeds the optimization in a simulation environment by taking full advantage of the sliding window approach and creating a loop for a continuous improvement of the optimized solution at each window of the sliding window approach. Both methods prove to be effective by improving the performance, lowering the total amount of conflicts up to 23.33% for the first method and up to 11.2% for the second method, however, in contrast to the deterministic method, the two methods they are not able to achieve a conflict-free scenario due to the effect of uncertainty.In general, the research conducted in this thesis highlights that uncertainty is a factor that affects to a large extent the feasibility of optimized solution when applied to real-world instances, and it, moreover, confirms that using simulation together with optimization has the potentiality toivdeal with uncertainty. The framework developed can be potentially applied to similar problems and different optimization solving methods can be adapted to it.Keywords: Optimization, Simulation, Integrated airport operations, Uncertainty

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Volkswirtschaftslehre : eine Einführung in ein oft verkanntes Fachgebiet

Dieses Lehrbuch gibt eine erste Einführung in die Volkswirtschaftslehre und gewährt allgemein verständliche Einblicke in die verschiedenenen Bereiche der Mikro- und Markoökonomik. Dabei reicht die Grundlagenvermittlung von der allgemeinen Einführung in das Fach der Volkswirtschaftslehre, über die Erklärung von Wirtschaftssystemen, Märkten und ihren Funktionsweisen bis hin zu der diese Ausführung ergänzenden praktischen analyse durch aktuelle Beispiele und vertiefende Informationen.

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Volkswirtschaftslehre : eine Einführung in ein oft verkanntes Fachgebiet

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Setting them free

One of the factors that differentiate honors from regular teaching at the Faculty of Geosciences at Utrecht University, the Netherlands, is the freedom that honors students enjoy, a freedom that evokes excellence because it is focused and targeted. This targeted freedom takes three different shapes in our honors program and comes with specific challenges for both students and teachers. While the attractions and advantages of such freedom are both theoretically and practically significant, our experience has also demonstrated drawbacks that need to be addressed and resolved in creating effective honors education.The challenges and struggles as well as the rewards that we have experienced might be familiar to honors educators around the world, but they are also shaped by the particular contexts of our program within the Faculty of Geosciences, within Utrecht University, and within the Netherlands, contexts that we will now introduce.

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A generic framework for modelling airport operations at a macroscopic level

In this paper, a general approach for modeling airport operations is presented. Airport operations have been extensively studied in the last decades ranging from airspace, airside and landside operations. Due to the nature of the system, simulation techniques have emerged as a powerful approach for dealing with the variability of these operations. However, in most of the studies, the different elements are studied in an individual fashion. The aim of this paper, is to overcome this limitation by presenting a methodological approach where airport operations are modeled together, such as airspace and airside. The contribution of this approach is that the resolution level for the different elements is similar therefore the interface issues between them is minimized. The framework can be used by practitioners for simulating complex systems like airspace-airside operations or multi-airport systems. The framework is illustrated by presenting a case study analyzed by the authors.

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A generic framework for modelling airport operations at a macroscopic level

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A Generic Framework for Modeling Airport Operations at a Macroscopic Level

In this paper, a general approach for modeling airport operations is presented. Airport operations have been extensively studied in the last decades ranging from airspace, airside and landside operations. Due to the nature of the system, simulation techniques have emerged as a powerful approach for dealing with the variability of these operations. However, in most of the studies, the different elements are studied in an individual fashion. The aim of this paper, is to overcome this limitation by presenting a methodological approach where airport operations are modeled together, such as airspace and airside. The contribution of this approach is that the resolution level for the different elements is similar therefore the interface issues between them is minimized. The framework can be used by practitioners for simulating complex systems like airspace-airside operations or multi-airport systems. The framework is illustrated by presenting a case study analyzed by the authors.

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A Generic Framework for Modeling Airport Operations at a Macroscopic Level

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Discussing patients’ insurance and out-of-pocket expenses during GPs’ consultations

Background: Generally, a significant portion of healthcare spending consists of out-of-pocket (OOP) expenses. Patients indicate that, in practice, there are often some OOP expenses, incurred when they receive medical care, which are unexpected for them and should have been taken into account when deciding on a course of action. Patients are often reliant on their GP and may, therefore, expect their GP to provide them with information about the costs of treatment options, taking into consideration their individual insurance plan. This also applies to the Netherlands, where OOP expenses increased rapidly over the years. In the current study, we observed the degree to which matters around patients' insurance and OOP expenses are discussed in the Netherlands, using video recordings of consultations between patients and GPs. Methods: Video recordings were collected from patient-GP consultations in 2015-2016. In 2015, 20 GPs and 392 patients from the eastern part of the Netherlands participated. In 2016, another eight GPs and 102 patients participated, spread throughout the Netherlands. The consultations were coded by three observers using an observation protocol. We achieved an almost perfect inter-rater agreement (Kappa = .82). Results: In total, 475 consultations were analysed. In 9.5% of all the consultations, issues concerning patients' health insurance and OOP expenses were discussed. The reimbursement of the cost of medication was discussed most often and patients' current insurance and co-payments least often. In some consultations, the GP brought up the subject, while in others, the patient initiated the discussion. Conclusions: While GPs may often be in the position to provide patients with information about treatment alternatives, few patients discuss the financial effects of their referral or prescription with their GP. This result complies with existing literature. Policy makers, GPs and insurers should think about how GPs and patients can be facilitated when considering the OOP expenses of treatment. There are several factors why this study, analysing video recordings of routine GP consultations in the Netherlands, is particularly relevant: Dutch GPs play a gatekeeper function; OOP expenses have increased relatively swiftly; and patients have both the right to decide on their treatment, and to choose a provider.

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Products 32

Opt-Sim approach for the gate allocation problem in covid-19 times

An optimization-simulation closed-loop feedback framework for modeling the airport capacity management problem under uncertainty

SIM-OPT in the Loop: Algorithmic Framework for Solving Airport Capacity Problems

Optimization-Simulation implementations for harmonizing operations at big airports

Volkswirtschaftslehre : eine Einführung in ein oft verkanntes Fachgebiet

Setting them free

A generic framework for modelling airport operations at a macroscopic level

A Generic Framework for Modeling Airport Operations at a Macroscopic Level

Discussing patients’ insurance and out-of-pocket expenses during GPs’ consultations

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Opt-Sim approach for the gate allocation problem in covid-19 times

An optimization-simulation closed-loop feedback framework for modeling the airport capacity management problem under uncertainty

SIM-OPT in the Loop: Algorithmic Framework for Solving Airport Capacity Problems

Optimization-Simulation implementations for harmonizing operations at big airports

Volkswirtschaftslehre : eine Einführung in ein oft verkanntes Fachgebiet

Setting them free

A generic framework for modelling airport operations at a macroscopic level

A Generic Framework for Modeling Airport Operations at a Macroscopic Level

Discussing patients’ insurance and out-of-pocket expenses during GPs’ consultations