Influence of COVID-19 on air travel - A scenario study toward future trusted aviation

Michelmann, Johannes; Schmalz, Ulrike; Becker, Axel; Stroh, Florian; Behnke, Sebastian; Hornung, Mirko

doi:10.1016/j.jairtraman.2022.102325

Cited by 19 publications

(9 citation statements)

References 41 publications

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“…Table 3 presents the de-icing tasks for each position using the flight departure order, i.e., the de-icing schedule is based on the planned departure sequence of the day. The sequence number describes the original departure order; for instance, (1,5) indicates that aircraft 1 and 5, belonging to the S\M models, are being de-iced at position 1 simultaneously at a given moment. Table 3 displaying only a subset of tasks, uses '...' to indicate tasks that are omitted and not shown.…”

Section: Experiments and Analysismentioning

confidence: 99%

“…This process ensures the removal of ice and snow accumulated on the aircraft's surface, ensuring a safer flight. With the recovery of the civil aviation industry, the significant increase in airport flights has accentuated the deficiency of de-icing resources, particularly in extreme weather conditions [1]. In cold weather conditions, aircraft awaiting takeoff may be susceptible to icing.…”

Section: Introductionmentioning

confidence: 99%

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Bi-Level Optimization for De-Icing Position Allocation and Unmanned De-Icing Vehicle Fleet Routing Problem

Liu,

Huang,

Han

et al. 2024

Biomimetics

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Aircraft icing due to severe cold and local factors increases the risk of flight delays and safety issues. Therefore, this study focuses on optimizing de-icing allocation and adapting to dynamic flight schedules at medium to large airports. Moreover, it aims to establish a centralized de-icing methodology employing unmanned de-icing vehicles to achieve the dual objectives of minimizing flight delay times and enhancing airport de-icing efficiency. To achieve these goals, a mixed-integer bi-level programming model is formulated, where the upper-level planning guides the allocation of de-icing positions and the lower-level planning addresses the collaborative scheduling of the multiple unmanned de-icing vehicles. In addition, a two-stage algorithm is introduced, encompassing a Mixed Variable Neighborhood Search Genetic Algorithm (MVNS-GA) as well as a Multi-Strategy Enhanced Heuristic Greedy Algorithm (MSEH-GA). Both algorithms are rigorously assessed through horizontal comparisons. This demonstrates the effectiveness and competitiveness of these algorithms. Finally, a model simulation is conducted at a major northwestern hub airport in China, providing empirical evidence of the proposed approach’s efficiency. The results show that research offers a practical solution for optimizing the use of multiple unmanned de-icing vehicles in aircraft de-icing tasks at medium to large airports. Therefore, delays are mitigated, and de-icing operations are improved.

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Section: Experiments and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bi-Level Optimization for De-Icing Position Allocation and Unmanned De-Icing Vehicle Fleet Routing Problem

Liu,

Huang,

Han

et al. 2024

Biomimetics

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“…They found that either giving easy credit to firms or injecting new money into households could moderate the impacts of the shock, and these two policies would be effective if strong enough. Taking into account the interdependencies among economic, environmental, and pandemic factors, three scenarios for the aviation industry’s recovery from the COVID-19 pandemic until 2030 were developed, including post-COVID digivation (it refers to a fast economic and air traffic recovery and tech companies entering the aviation market, followed by extensive digitization efforts), clean restart (a strong customer focus on environmentally friendly means of transport after the pandemic is constrained), green and clean new normal (the slowest economic recovery and it deals longest with COVID-19-related hygiene measures) ( Michelmann et al, 2022 ). A fast economic recovery was observed in many sectors, while aviation being one of the hardest hit.…”

Section: Literature Reviewmentioning

confidence: 99%

A data-driven analysis of the aviation recovery from the COVID-19 pandemic

Sun

Wandelt

Zhang

2023

Journal of Air Transport Management

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“…Furthermore, it should be noted that, according to the data presented in Figure 1, a significant increase in air passenger demand is expected in 2022, with an increase of about 51% compared to the previous year. The COVID-19 pandemic is considered to be the most severe civil aviation crisis since World War II [19].…”

Section: Analysis Of Air Passenger Flow At the Global Levelmentioning

confidence: 99%

Structural analysis of air passenger flow in the Republic of Croatia from the COVID–19 pandemic impact perspective

2022

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Air transport is a globally significant mode of transport that carries people and goods over relatively long distances in a relatively short time. In the case of the Republic of Croatia there are some relevant geographical factors that make it necessary to connect the country to domestic and international airlines, such as territorial division (Dubrovnik’s disconnection from the rest of the Croatian mainland), rugged shape and mountainous terrain. In addition, as a tourist destination, the country should offer good transport links to provide the best experience for tourists. The aim of this research is to conduct an in-depth structural analysis of the intensity and dynamics of passenger air traffic at the global, European, and national (i.e. Croatian) level, considering the specific crisis of the COVID-19 pandemic as a relevant factor in the development of passenger flow. To achieve the defined objective of this research, a structural analysis of the relevant indicators for the development of passenger flow at the airports of the Republic of Croatia was conducted. In addition, a comparative analysis of the intensity, structure and dynamics of passenger flow was carried out within the framework of a comparison of the relevant criteria and statistical data on the indicators of passenger flow at the international, regional, and national levels. The COVID-19 pandemic has significantly affected the state of passenger flow in air transport in terms of organisation and logistics, and especially in terms of the intensity and dynamics of passenger flows. Accordingly, uniform criteria for monitoring passenger flow, systematisation and structural analysis of relevant formation indicators are the basic requirements for continuous monitoring and planning of passenger flow in air transport.

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Influence of COVID-19 on air travel - A scenario study toward future trusted aviation

Cited by 19 publications

References 41 publications

Bi-Level Optimization for De-Icing Position Allocation and Unmanned De-Icing Vehicle Fleet Routing Problem

Bi-Level Optimization for De-Icing Position Allocation and Unmanned De-Icing Vehicle Fleet Routing Problem

A data-driven analysis of the aviation recovery from the COVID-19 pandemic

Structural analysis of air passenger flow in the Republic of Croatia from the COVID–19 pandemic impact perspective

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