Airline Network Research Articles

Modeling and analysis of COVID-19 spreading based on complex network theory

Complex networks can effectively describe interactions within real-world complex systems. In researches of epidemic spreading, scientists constructed various physical contact networks between individuals on the microscopic scale and the metapopulation networks on the macroscopic scale. These different types of network structures significantly impact the propagation dynamics of epidemic in human society. For instance, population flows in global airline networks influence the speed and arrival time of epidemics across large-scale space. In this paper we review the epidemic spreading models on various network structures, including fully mixed networks, three types of lower-order networks, three types of higher-order networks, metapopulation networks, and multiple strains competitive epidemic spreading models. We also provide an overview of the application of complex network theory in the COVID-19 pandemic, covering topics of prediction, prevention, and control of the epidemic. Finally, we discuss the strengths and limitations of these models and propose perspectives for future research.

Resilience of weighted networks with dynamical behavior against multi-node removal.

In many real-world networks, interactions between nodes are weighted to reflect their strength, such as predator-prey interactions in the ecological network and passenger numbers in airline networks. These weighted networks are prone to cascading effects caused by minor perturbations, which can lead to catastrophic outcomes. This vulnerability highlights the importance of studying weighted network resilience to prevent system collapses. However, due to many variables and weight parameters coupled together, predicting the behavior of such a system governed by a multi-dimensional rate equation is challenging. To address this, we propose a dimension reduction technique that simplifies a multi-dimensional system into a one-dimensional state space. We applied this methodology to explore the impact of weights on the resilience of four dynamics whose weights are assigned by three weight assignment methods. The four dynamical systems are the biochemical dynamical system (B), the epidemic dynamical system (E), the regulatory dynamical system (R), and the birth-death dynamical system (BD). The results show that regardless of the weight distribution, for B, the weights are negatively correlated with the activities of the network, while for E, R, and BD, there is a positive correlation between the weights and the activities of the network. Interestingly, for B, R, and BD, the change in the weights of the system has little impact on the resilience of the system. However, for the E system, the greater the weights the more resilient the system. This study not only simplifies the complexity inherent in weighted networks but also enhances our understanding of their resilience and response to perturbations.

Carbon pricing and airline network selection: A four-network perspective

This paper investigates how variations in aviation carbon pricing influence the network choices of airlines and social planner. Beyond the traditional direct-flight (DF) network, hub-and-spoke (HS) network and mixed (MX) network, we incorporate the 2-hub (2 H) network into our analysis. The findings reveal that as carbon pricing costs increase, the optimal network configuration for airlines progresses sequentially through 2 H, MX and DF. This suggests that due to horizontal product differentiation, the inclusion of 2 H in the model renders the HS network—which is widely utilized by numerous major airlines—no longer the optimal choice for airlines. From the perspective of social planner, the optimal network configuration undergoes a progression from HS, 2 H, HS, MX, DF, MX to DF as carbon pricing costs rise. While the HS network may not align with the optimal choice for airlines, it has the potential to be the socially optimal network. Furthermore, the transition of socially optimal networks exhibits discontinuities, resulting in significant deviations from the network decisions made by airlines. Overall, this paper broadens the scope of network choices available to airlines by incorporating the 2 H network and offers theoretical insights for policy formulation by both airlines and society within the context of aviation carbon offset.

Impacts of COVID-19 on Air Traffic Control and Air Traffic Management: A Review

The global air transportation system continues to be greatly impacted by operational changes induced by the COVID-19 pandemic. As air traffic management (ATM) focuses on balancing system capacity with demand, many facets of ATM and system operations more broadly were subjected to dramatic changes that deviate from pre-pandemic procedures. Since the start of the COVID-19 pandemic when air travel became one of the first transport modes to be impacted by lockdown procedures and travel restrictions, a geographically diverse cohort of researchers began investigating the impacts of the COVID-19 pandemic on air navigation service providers, airline and airport operations, on-time performance, as well as airline network structure, connectivity, crew scheduling, and service impacts due to pilot and crew shortages. In this study, we provide a comprehensive review of this aforementioned body of research literature published during one of the most tumultuous times in the history of aviation, specifically as it relates to air traffic management and air traffic control. We first organize the reviewed literature into three broad categories: strategic air traffic management and response, air traffic control and airport operational changes, and air traffic system resilience. Then, we highlight the main takeaways from each category. We emphasize specific findings that describe how various aspects of the air transportation systems could be improved in the domestic and global airline industry post-COVID. Lastly, we identify specific changes in operational procedures due to the COVID-19 pandemic and suggest future industry trends as informed by the literature. We anticipate this review article to be of interest to a broad swath of aviation industry and intercity transportation audiences.

A modified radiation model based on the characteristics of airline network under large-scale disruptions

A modified radiation model based on the characteristics of airline network under large-scale disruptions

Destination selection and flight scheduling for regional airlines at slot‐constrained airports

AbstractWe present the problem of a regional airline based at a slot‐constrained airport, which must select a set of destinations to serve, how many flights per day to operate to each destination, at what time the flights take place and which aircraft operates each flight. Restricting ourselves to the special case of regional airlines, which fly round trips from a central hub, we are able to tackle the four above decisions jointly. By contrast, in the existing literature, these decisions are usually optimised separately for generic airline networks. To solve the proposed problem, we introduce two compact integer formulations: a three‐index and a two‐index formulation. This latter, however, only solves a relaxation of the original problem because it cannot guarantee that all constraints are respected. Therefore, we embed the two‐index formulation into an iterative algorithm which dynamically adds violated constraints. Computational experiments highlight the validity of this approach and provide insights into the characteristics of the solutions.

Flight delay propagation in the multiplex network system of airline networks

The flight delay propagation and recovery processes in airline networks differ due to differences in airline network structures, capacity distributions, and base airport locations. When each airline network is regarded as a network layer, flight delay propagation and interaction in a multiplex network system (MNS) composed of multiple airlines will become more complex and variable. In this paper, flight delays from different airlines are considered propagation sources, and an MNS-based flight delay propagation model is established under the framework of the susceptible-infected-susceptible model. By comparing the independent propagation process of delays in a single-layer airline network and the interactive propagation process of delays in an MNS, we investigate the impact of network structure on flight delays to propose corresponding delay control strategies for different airlines. The results show that unlike in single-layer networks, in an MNS, the behavior of airlines at an airport facilitates or inhibits delay propagation in other layers by influencing the network characteristics and propagation rate. The same airport may even play different roles in different layers, depending on the function it has. Therefore, not all flights are infected or have aggravated delays when accessing the MNS; instead, they are impacted by combined factors such as on-time performance, network structure, and flight interaction.

Analysis of Approaches to Assessing Flight Delays Due to Technical Issues at Airline Network Airports Within the Operational Management Framework

ABSTRACT This paper analyzes approaches to developing models for the technical exploitation (TE) of aircraft within operational management framework. The operational management contour of the TE of the airline’s AC fleet is considered as a TE process consisting of a sequence of flight routes, which, in turn, comprise a sequence of flights between airports in the airline network during the calendar interval when the aircraft are in this contour. We present a model that evaluates the capacity for aircraft recovery at the network airports of a hypothetical airline (dubbed “RAF”) if the need so arises, utilizing the probabilistic and temporal characteristics of the airports used for aircraft recovery.

Modeling the Regional Distribution of International Travelers in Spain to Estimate Imported Cases of Dengue and Malaria: Statistical Inference and Validation Study.

Understanding the patterns of disease importation through international travel is paramount for effective public health interventions and global disease surveillance. While global airline network data have been used to assist in outbreak prevention and effective preparedness, accurately estimating how these imported cases disseminate locally in receiving countries remains a challenge. This study aimed to describe and understand the regional distribution of imported cases of dengue and malaria upon arrival in Spain via air travel. We have proposed a method to describe the regional distribution of imported cases of dengue and malaria based on the computation of the "travelers' index" from readily available socioeconomic data. We combined indicators representing the main drivers for international travel, including tourism, economy, and visits to friends and relatives, to measure the relative appeal of each region in the importing country for travelers. We validated the resulting estimates by comparing them with the reported cases of malaria and dengue in Spain from 2015 to 2019. We also assessed which motivation provided more accurate estimates for imported cases of both diseases. The estimates provided by the best fitted model showed high correlation with notified cases of malaria (0.94) and dengue (0.87), with economic motivation being the most relevant for imported cases of malaria and visits to friends and relatives being the most relevant for imported cases of dengue. Factual descriptions of the local movement of international travelers may substantially enhance the design of cost-effective prevention policies and control strategies, and essentially contribute to decision-support systems. Our approach contributes in this direction by providing a reliable estimate of the number of imported cases of nonendemic diseases, which could be generalized to other applications. Realistic risk assessments will be obtained by combining this regional predictor with the observed local distribution of vectors.

Layout analysis of the RCEP international airline network based on hub identification using improved contribution matrix

The signing of the Regional Comprehensive Economic Partnership agreement brings new opportunities for the development of international air transportation. Faced with fierce competition, it is worth studying how hub airports should enhance competitiveness, and how low-cost carriers and full-service carriers should optimize the RCEP international airline network layout for better development. Aiming at providing suggestions for the development of hub airports, low-cost and full-service carriers in the RCEP international airline network, this paper identifies the hub airports, analyzes the layout of the RCEP international airline network, and the multi-layered characteristics based on an improved contribution matrix using data from 2010 to 2019 collected from the Official Airline Guide (OAG). This method comprehensively considers attributes of hub airports and the multi-layered characteristics of the airports and routes. The layout analysis indicates that the RCEP international transportation market presents a more open environment for competition and cooperation where base carriers are often the biggest supporters of hub construction. The multi-layered characteristics analysis reveals that low-cost carriers contribute more towards opening up new RCEP routes than full-service carriers. It is advised that carriers newly entering the RCEP international aviation transportation market and low-cost carriers dedicate to establishing new routes around their hub airports to monopolize this market and enhance their market share, whilst full-service carriers consolidate existing routes and increase route density to achieve economic benefits.

Analyzing Mathematical Models in the Transition to Network-Based Revenue Management: A Comprehensive Review

Airlines have expanded hub-and-spoke networks, leading to a notable rise in the importance of network-based revenue management systems. In their pursuit to maximize overall revenue, an airline's network RM-based system differentiates between local passengers using single resources and connecting or flow passengers utilizing multiple resources. Despite being theoretically ideal, these systems can be difficult to implement directly in real-world scenarios. The implementation of such systems often relies on assumptions that may lead to suboptimal decisions if incorrect. This article aims to outline the primary challenges practitioners may encounter during the transition to a network-based RM system. It begins with a brief overview of typical network-based RM models and then delves into three areas where this system could potentially lower an airline's revenue: forecasting optimization, and distribution. The goal is to elucidate each of these areas and their respective difficulties related to implementing a network RM system in detail so that fellow researchers can consider them within the field of network RM while providing practitioners insights for addressing these issues during the implementation process within their organization Key Words: Airline hub-and-spoke networks, Revenue management, network-based RM models, forecasting, network optimization, distribution.”

Prediction of environmental benefits introducing hybrid-electric propulsion on regional aircraft

The objective of this paper is to assess the environmental benefits arising from the introduction of hybrid-electric propulsion on regional and commuter turboprop aircraft. A great focus is put on the propulsion based on a turbine engine coupled with batteries, combining mature technologies. The introduction of novel propulsion architectures on aircraft deployed on regional and commuter networks allows a substantial reduction of the fuel needed by airlines. In this work, scenarios based on real airline networks are presented, in order to quantify the reduction of greenhouse gas emissions possible considering the expected technological advancement for 2035 and 2050. This analysis is conducted by retrofitting the hybrid-electric propulsive system onto existing aircraft that can carry 19 passengers (Dornier DO228) or 70 passengers (ATR72-600). For the 19-seat class, a clean sheet design is also considered to overcome some limitations of the reference aircraft. A precise assessment of the peculiarities linked to the chosen propulsive configuration shows that networks that have shorter flights are better suited to the introduction of this technology, as the restriction on the design payload is less stringent. The proposed propulsive architecture allows a reduction of the operators’ yearly fuel budget of up to 50% in 2035 and 80% in 2050. At last, the taxi phase is of particular importance for regional aircraft that perform several rotations a day, therefore a further analysis of this phase is carried out. The result shows that the considered aircraft are capable of completing a full Landing & Take-Off (LTO) cycle without resorting to the thermal part of the propulsive system, reducing considerably the impact of the aircraft on the airport area.

A multi‐emission‐driven efficient network design for green hub‐and‐spoke airline networks

A multi‐emission‐driven efficient network design for green hub‐and‐spoke airline networks

Study on “three places and four fields” airline resource cooperative allocation based on decision tree algorithm

In view of the disharmony development status of Beijing Tianjin Hebei region, the paper puts forward a route optimization Principle of cooperative allocation of route resources of airport group from the angle of flight punctuality, airlines share and function orientation. An optimal model of airline resources cooperative allocation is established to maximize the overall operational benefit of regional airports and the modified decision tree C4.5 algorithm was applied to solve the problem. Since this algorithm combined with constraint condition of model as pruning standard, the efficiency of the algorithm was greatly improved. Finally, the problem find the optimal solution could be found by comparing the profit and loss value of the program. The analysis example showed that the overall benefit of multi-airport system increased by 7.03%. This model was useful to optimize airline network and conformed to the actual situation, and the research results can provide a reference for civil aviation authorities in planning the airline network of multi-airport system.

Weighted chained graphs and some applications

This paper introduces weighted chained graphs, as well as minimal broadcasting and receiving sets, and investigates their properties. Both directed and undirected graphs are considered. The notion of central nodes is introduced both for weighted directed and undirected graphs. This notion is helpful for determining how quickly information can propagate throughout a graph. In particular, it is useful for the investigation of transportation networks and for city planning. Applications to the analysis of airline and bus networks are presented.

Historical evolution and characteristics of the airline network in Japan

Historical evolution and characteristics of the airline network in Japan

A multi‐emission‐driven efficient network design for green hub‐and‐spoke airline networks

AbstractThe green hub‐and‐spoke airline network (GHSAN) is emerging as a dominant feature due to its excellent economic and environmental‐friendly capabilities. However, environmental GHSAN designs still have some concerns, including single pollutant‐domain oversimplification and lack of comprehensive network‐level operation impacts. This paper proposes a multi‐emission‐driven efficient network design approach for GHSAN, utilizing a system, green, and user threefold optimization methodology. The approach includes a multi‐objective optimization model and a two‐layer solving method. The multi‐objective optimization aims at minimizing multiple emissions, including carbon dioxide, carbonic oxide hydrocarbon, and nitric oxide, while also considering transportation system costs and journey user costs. A two‐layer optimization algorithm is adopted to address different scales of optimization. Real‐world results demonstrate that the proposed method mitigates environmental impact and user costs and increases overall airline density in airline networks. The proposed method can have a 16.29% reduction in green‐fold (10 nodes) and a 12.06% decrease in user costs for the user‐fold (10 nodes). As the number of nodes (15, 25, 50 nodes) and hubs (3, 4, 5, 6, 7 hubs) increase, the genetic algorithm (GA) proves to be more efficient and suitable in large‐scale GHSAN. This work is further significant for the long‐term and sustainable development of the future air transport industry.

It's not simply luck: The impact of network strategy, schedule padding, and operational improvements on domestic on‐time performance in the US airline industry

Airlines showcase their on‐time performance (OTP), a globally accepted operational performance metric, to demonstrate punctuality, service reliability, and attract air travelers. Airlines can adopt passive strategies, such as “schedule padding,” and active strategies, such as making “operational changes/improvements,” to improve their OTP. While there is a high degree of variation in airlines' OTP from year to year, it is unclear if and the extent to which airlines' active or passive actions impact their OTP because of factors, like weather, outside an airline's control. We develop a framework in this paper to study the impact of these active and passive actions on the OTP of airlines. Additionally, we study the effect of these strategies on OTP rankings, routinely used to compare airlines. Our methodology builds on the structural estimation model developed in prior literature and replicates the typical schedule planning process observed in the airline industry. We use an 11‐year panel data of flights operated by US domestic carriers from 2005 to 2015 to measure OTP changes, schedule padding, and operational changes. Broadly, active actions include (i) changes to the airline's network structure (e.g., flight routes and schedules) and (ii) other operational changes to improve flight performance (operational improvement). We demonstrate through our analysis that operational improvements have the highest association with both the change in OTP and OTP rankings of airlines, followed by schedule padding; the impact of network changes on OTP and OTP rankings is the lowest. Our framework also accounts for the impact of competition on an airline's OTP ranking. We show that while an airline's own actions can improve its OTP ranking, a competitor's action may negatively affect the ranking. In fact, a competitor's passive strategy of schedule padding may have a higher impact than an airline's own active strategy of changes in network structure. Our results also indicate that the potential impact of operations improvements is the highest for full‐service airlines and the lowest for leisure airlines. Furthermore, we show that the impact of operational improvements and buffer adjustments decreases with an increase in the variability of the travel time of a route.

Contrasts in Sustainability between Hub-Based and Point-to-Point Airline Networks

Airline hubs are often defined as nodes with a high degree of connectivity. Connectivity is measured by the “degree” of the node. The degree distribution of hub networks tends to have a convex shape (curved towards the origin), while point-to-point networks have a higher number of high-degree nodes and a concave shape. This study aims to classify airline networks based on their hub orientation, expanding our understanding of network differences. The analysis in this paper involves fitting a power-law distribution, determining the range of degree distribution, and calculating the distribution of betweenness. These analyses provide insight into the classification of each airline. Each measurement helps to clarify the ambiguity in other scores. The goal is to establish a small set of rules that can clearly distinguish between the main types of networks. The classification includes four types of networks: One-hub, P2P(point-to-point), Multi-hub, and Complex networks. There is a well-recognized empirical distinction between hub networks, which have a few places with large betweenness, and point-to-point cases, which have a larger number of places with moderate betweenness. The significance of these results in terms of geographic importance is demonstrated by sorting 284 different airline networks based on these dimensions. These findings are expected to provide valuable information about the resilience and recovery of a network, as networks with many long-range connections are particularly vulnerable to a decrease in traffic. Additionally, these results have implications for the ability of networks to recover from a downturn.

Disruption and recovery of the US domestic airline networks during the COVID-19 pandemic

The COVID-19 pandemic has had serious impacts on the airline industry. Ensuring that aviation policies in emergent situations both guarantee network connectivity and maintain competition among airlines is crucial in these circumstances. To this end, we aimed to understand the network dynamics of individual airlines. In this study, we quantitatively reveal the day-to-day dynamics of these US domestic airline networks, comprising 17 airlines, from January 2019 to December 2021. Specifically, we applied a framework for analyzing temporal networks, in which the network structure changes over time. We found that, first, even though the number of nodes and edges returned to pre-pandemic levels around July 2021, the structure of the entire US domestic airline network remained altered. We also found that the network dynamics varied significantly from airline to airline. Full-service carriers were less flexible in changing their network structure and suffered higher revenue losses. On the contrary, most regional carriers completely shifted to a new structure, which may have contributed to reducing their revenue losses. Low-cost carriers were characterized by more pronounced differences between airlines and drastically changed their network structure immediately after the declaration of a national emergency. Finally, we also examined the recovery process and found that the flights connecting airports that are more central and share more common neighbors, and those connecting airports with larger numbers of connections tend to recover earlier for most of the airlines.