Air Transportation Network Research Articles

Transport network backbone extraction: A comparison of techniques

Network backbone extraction techniques reduce the size of networks while trying to preserve their key topological and spatial features. Various backbone extraction algorithms have been proposed in different scientific fields. Although of clear interest to transport geographers, backbone extraction techniques have been adopted unevenly and in an ad hoc fashion in transport geography research. In this paper we therefore present a conceptual and experimental comparison of backbone extraction techniques in a transport-geographical context, and explore the new insights each technique can offer to enhance our understanding of the Southeast Asian intercity air transport network (SAAN). We review six frequently-used methods, i.e. global weight thresholding method (GWTM), k-core decomposition method (KCDM), minimum spanning tree method (MSTM), primary linkage analysis method (PLAM), multiple linkage analysis method (MLAM), and the disparity filter algorithm method (DFAM), and elaborate their analytical essence by applying them to extract the backbone of the SAAN. The abstracted networks are compared in terms of their geographical and topological structures using the initial network as a benchmark. This comparison is then used to point out the different techniques' potential in light of different transport geography research applications.

The RINGO project, identifying research infrastructure needs and gaps to foster innovation in aeronautical research in Europe

In this paper the RINGO (“Research Infrastructures - Needs, Gaps and Overlaps”) project and its methodology as well as initial findings will be presented. RINGO is a Coordination and Support Action funded by the European Commission under H2020 aimed at delivering a cohesive and coordinated approach for the identification and assessment of the needs, gaps and overlaps for strategic aviation research infrastructures in Europe; and at analyzing potential sustainable business models and funding schemes for the maintenance and improvement of existing and development of new research infrastructures. During its first year RINGO is producing a preliminary report concentrating on the needs and gaps for research infrastructure needed to work towards the goals laid out in the strategy document Flightpath 2050 produced by ACARE, the Advisory Council for Aviation Research and innovation in Europe. Flightpath 2050 has provided Europe with a vision for aviation and air transportation, identifying goals for the research community and policy makers alike. Based on this vision ACARE has also developed the SRIA (Strategic Research and Innovation Agenda) which serves as a roadmap for aeronautical research for the next decades. RINGO will start from these and other similar documents to identify research infrastructures that are key to European aeronautical research. The identification of these needs will be performed by expert interviews, ensuring a broad coverage of all relevant topics. These interviews will be carefully prepared and staged to ensure full coverage of the FP2050 goals. In parallel RINGO will create a catalogue of existing RIs, starting from the research infrastructures Catalogue that has previously been developed by the AIRTN (Air Transport Network) project. This catalogue will be enhanced with data from other sources and a comprehensive database of European research infrastructure will be established. Comparing the needs identified in the first step and the available infrastructures will yield information about gaps and also overlaps. During the first iteration only a limited view will be produced, covering only some key areas and interviewing only a small group of experts, mainly from ACARE working groups and similar bodies. At the same time a limited catalogue of existing infrastructures will build. This will allow the project to produce a preliminary report as a first input to policy makers at European level. In the second iteration the process will be repeated more thoroughly, interviewing a broader range of experts and adding more detail to the catalogue as well. The final result will be a comprehensive report on RI Needs, Gaps and Overlaps, which is seen as a valuable input to the research community as well as to policy makers.

Reliability evaluation of a multi-state air transportation network meeting multiple travel demands

In last decades, air transportation plays an important role in global economy. Several scholars have studied optimizing air transportation system or proposed reliability evaluation algorithms from airline management viewpoints. This work evaluates the reliability of an air transportation system from the perspective of travel agency instead. An air transportation system can be modeled as a multi-state air transportation network (MATN) wherein each node represents an airport and each arc denotes a flight carrying passengers between a pair of airports from scheduled departure time to scheduled arrival time. Significantly, this study focuses on investigating the reliability of multiple travel demands. Therefore, the reliability of an MATN is defined as the probability that a set of demands can be carried successfully under constraints of time and number of stopovers. This study employs the concept of minimal paths in reliability evaluation. Subsequently, a searching procedure is added to the proposed algorithm. In addition, an illustrative example and a case study are utilized to demonstrate the proposed algorithm and discuss the implications of reliability evaluation for the management of travel agency.

The evolving structure of the Southeast Asian air transport network through the lens of complex networks, 1979–2012

This paper presents a novel approach to investigating and understanding the evolving structure of the Southeast Asian air transport network (SAAN) over the period 1979–2012. Our approach captures the main topological and spatial changes from a complex network perspective. We find that the SAAN combines a relatively stable topological structure with a changing multilayered geographical structure. Statistical analysis indicates that the SAAN is a scale-free network with an increasing number of hub cities and has been characterized by small-world properties since 1996. Furthermore, the SAAN exhibits a recently intensified disassortative mixing pattern, suggesting an increasing dependence of small cities on hub-and-spoke configuration for better accessibility. A decomposition analysis is used to disaggregate the SAAN into a hierarchical core-bridge-periphery structure. The core layer consists of capital cities, the most economic vibrant secondary cities, and tourist destinations. This core layer is also densely interconnected with its center of gravity moving towards the north. The periphery layer, comprised of cities in remote areas, sustains a low significance with declining internal connectivity despite a rising number of cities being connected. The bridge layer lies in between both extremes, and is characterized by a high volatility over time. The connections and passengers between different layers increase, especially those between core and bridge after 1996. In our discussion, we trace these changes back to a series of socio-economic and politico-institutional dynamics in Southeast Asia.

Integrators’ Air Transport Networks in Europe

Integrators are shipping carriers that control complete air and road delivery networks and offer a wide range of package delivery services. Despite the increasing relevance of small package delivery services in the European air transport market, very little has been written on integrated carriers’ air transport networks on the Old Continent. In this paper we examine the network configurations of DHL, FedEx, TNT, and UPS in terms of hubs, spokes, and market shares. Our results show that integrators operate hub-and-spoke networks. Network indices and centrality measures confirm that their network structures are more similar to those of full-service passenger carriers rather than those of low-cost carriers. However, the nature of their hub-and-spoke systems is different because freight tons, as compared to passengers, are more easily flown along multiple-stop and circular routes. As a consequence, FedEx, TNT, and UPS operate non-pure star networks with a dominant central hub and a set of intermediate airports acting as stops between the central hub and (usually) one “external airport”. DHL operates a multi-hub architecture, with a main dominant hub in Leipzig and a set of “secondary hubs” that provide several connections to other network nodes. Furthermore, we provide evidence of the most important intra-Europe and long-haul routes for each integrator, showing that DHL seems to have a more developed Europe-Asia connection, and is the only integrator to connect Europe to Sub-Saharan Africa. Finally, we show the high degree of complementarity existing between FedEx and TNT networks and that such complementarity is confirmed also by an analysis of their market shares in the different European sub-markets. Despite the significant level of market concentration, our analysis shows that the recent merger between FedEx and TNT is not expected to significantly modify market equilibrium in Europe.

Measuring the vulnerability of community structure in complex networks

This paper develops a quantitative method to measure the vulnerability of community structure with emphasis on both internal and external connectivity characteristics of the community. In particular, the number of links between communities and the strength of links connecting two communities are considered as external factors, while the connection density, the degree of gateway nodes, as well as the strength of links within each community are treated as internal factors. A non-linear weighted function is used to combine the internal factors with external factors. Then the developed method is used to illustrate the vulnerability analysis of community structure of a power transmission grid, a karate club network, and an air transportation network. The results reveal that the proposed measure is effective in differentiating the vulnerability level of community structure in a variety of networks.

Simulating air transportation networks under capacity constraints

PurposeCongestion as a consequence of the rapidly growing air traffic is one of the outstanding problems of the air transportation industry. Traffic impediment rates, having an increasing acceleration while the airport capacities have been kept constant due to several reasons, cause problems such as arrival/departure delays, schedule interruptions, cancellations and customer dissatisfaction. In this paper, the author aims to study transitioning from a single-hub air transportation system to a multi-hub infrastructure via Monte Carlo simulation.Design/methodology/approachThe current hub has reached its capacity limits for long so that the growth potential of the air transportation has been affected adversely. One of the possible remedies suggested by authorities, professionals and academics was to transform the air transportation infrastructure into a multi-hub setting. Current air traffic of the country was modeled by means of simulation. Airport capacities and performances are simulated and analyzed under different scenarios considering a potential alternative hub along with the central one. Possible delays in both hubs are studied in case of moderately increasing traffic congestion.FindingsAs a result, decreased delay levels in the central hub are observed, whereas no delays are experienced in the potential one in all the scenarios.Originality/valueThis study, proposing to organize the national and international air traffic of the country while harmonizing the delay rates and increasing the passenger satisfaction, is to contribute significantly to the aviation sector companies, airliners and airport operators by shedding light on the imminent capacity issues air transportation industry is going to face.

Characterizing the dynamics underlying global spread of epidemics

Over the past few decades, global metapopulation epidemic simulations built with worldwide air-transportation data have been the main tool for studying how epidemics spread from the origin to other parts of the world (e.g., for pandemic influenza, SARS, and Ebola). However, it remains unclear how disease epidemiology and the air-transportation network structure determine epidemic arrivals for different populations around the globe. Here, we fill this knowledge gap by developing and validating an analytical framework that requires only basic analytics from stochastic processes. We apply this framework retrospectively to the 2009 influenza pandemic and 2014 Ebola epidemic to show that key epidemic parameters could be robustly estimated in real-time from public data on local and global spread at very low computational cost. Our framework not only elucidates the dynamics underlying global spread of epidemics but also advances our capability in nowcasting and forecasting epidemics.

Gravitational analysis of the air transport network. Application to the case of Colombia

Abstract In this paper the gravity model is used to analyze the flow of domestic passengers by air transport between the main airports of a network. To apply the model, the airport network of Colombia is used as a case study. To do this, different analysis with various types of areas of influence and explanatory variables are used. When comparing the results with those from other studies, when the ranges of distances are consistent and these results are conclusive, the regression analysis confirms that due to the particular conditions of the network of Colombian air transport (geography, location of airports, lack of alternatives to air transport) distance is a factor that drives rather than deters air passenger movement and can be considered a priority with the gravity model.

Governing Competition and Collaboration in Network Industries Using Agent-Based Modeling: A Case-Study of US Air Transportation Network

Network industries include a multitude of organizations and companies delivering valuable services and products for modern life. Surprisingly, the impact of the structural complexity of their underlying physical infrastructure on the behavior of these organizations has not been explored yet. The aim of this paper is to study the role of an initial network structure on the throughput of these complex systems, and to provide evidence for the value of using agent-based modeling (ABM) in governing competition and collaboration in network industries. A two-stage multiround game provides the mathematical foundation to examine the behavior of players in the complex interconnected structure of a network industry. The United States Air Transportation Network is used as the case study. The real data on the different elements of the system are embedded into an agent-based model to provide a descriptive model of behaviors within it. The outcome of the model shows path dependence in the system and highlights the impact of initial network conditions on the market. Moreover, this model provides evidence on the usefulness of ABM for understanding the interrelationships between economic behavior and the physical structure of the system.

Complementary strengths of airlines under network disruptions

Disruptions of air transportation systems, caused by events such as, extreme weather conditions or human-intended attacks, can lead to huge economic losses. Existing studies have modeled and estimated the robustness of air transportation networks under node/link failures, and found that networks disintegrate quickly under targeted attacks. The robustness of airline networks, however, has been largely neglected in the past, with investigating strongly spatially constrained regions and few airlines only.In this study, we first investigate the robustness of more than 200 global airline networks, which cover almost 95% of worldwide air passenger transportation. We find that the robustness depends largely on the structure of the airline network. Second, we estimate how much these disruptions can be absorbed by other airlines using the notion of static complementary strength. In addition, with passenger data and rerouting considerations, we analyze how much of an airline disruption can be compensated by other airlines in reality. Results show that the traditional complementary strength clearly overestimates the robustness of the network; according to our more realistic model, many airlines are indeed easy to fail and the consequences of failures are not readily compensated by other airlines. Our work contributes towards improving air transportation systems, by understanding the hidden threats of airline disruptions.

The transition point of the Chinese multilayer air transportation networks

The air transportation network across a certain area, a typical multilayer complex system, is composed of a number of individual airlines, each of which forms a single layer. A central problem in airline merging is the minimal number of layers, denoted by [Formula: see text], that is needed for the merged network to function nearly as well as the fully aggregated network. For this purpose, we monitor several structural measures during the network aggregation process in which [Formula: see text] is gradually increased. For China Air Transportation Network (CATN), we identify a common, sharp transition point yielding [Formula: see text]. Whereas, for European Air Transportation Networks (EATN) there is no clear signal of such a transition point. The transition point of CATN is confirmed by means of the Wasserstein distance and the relative entropy. Our results indicate that there is still room in the optimization of CATN while for EATN, it seems better to keep the present structure.

A bi-objective, reliable single allocation p-hub maximal covering location problem: Mathematical formulation and solution approach

In the last few years, the p-hub maximal covering problem (pHMCP) has been applied in a variety of applications, including the design of air transportation networks, distribution systems for perishable products, postal delivery networks, and tourism routing. In hub-based systems, disruptions at hubs or unavailability of routes significantly affect service level and result in excessive costs. To tackle these problems, selecting backup hubs for unavailable hubs and rerouting the related flows are often proposed. This paper develops a bi-objective reliable single allocation p-hub maximal covering problem (BRSApHMCP) considering two objectives: maximizing expected covered flows and minimizing congestion. After formulating an initial non-linear model, a linear model is presented; the NP-Completeness of the developed model is proved and a non-dominated sorting genetic algorithm (NSGA-II) is proposed to solve it. In order to show the superior performance of the proposed NSGA-II, a well-known evolutionary algorithm, the multi-objective particle swarm optimization (MOPSO), and the epsilon constraint methods are utilized and the results are analyzed and compared. The parameters of the proposed algorithms are calibrated using the Taguchi approach. Also, a case study and some parametric analyses are done. The results show that NSGA-II is able to find the better solutions in comparison with MOPSO and by opting this proactive strategy in the investigated case study, NSGA-II could recover up to 73% of lost flow in a well-balanced system.

Global network centrality of university rankings.

Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport’s aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity.

Analysis of the Air Transport Network Characteristics of Major Airports

ABSTRACT The world's major airports are directly connected to hundreds of airports without intermediate routes. This connectivity can be described as the network in which the airport becomes a node and the route becomes a connection line. In this regard, this study analyzes the air transport network of 1,060 airports using the social network analysis (SNA) methodology. We consolidated the data from three airline alliances and established a network of 1,060 airports and 5,580 routes in 173 countries. Many previous studies on air transport network examined several specific airports or regions and mainly utilized the internal indicators of airports. Conversely, this study conducted a comprehensive analysis covering 173 countries by using air route, which is an external indicator of airports. This study presented the general characteristics of major countries and regions from the perspective of SNA and compared the individual networks of the United States and China, which have the greatest influence on international air logistics within the scope of the entire network analysis. This study can aid in the understanding of air transport networks and logistics connectivity in inter-city and inter-country transport.

ANALISIS KONEKTIVITAS JARINGAN TRANSPORTASI UDARA NASIONAL

The airport as flight network node is the starting point and the end of the movement of people/goods. The airport can also be a transit point before continuing the journey to the destination. The closure of the airport due to force majeure such as a disaster or terrorism may disrupt the national air transportation network. The effects of the closure of an airport to the national air transportation network depends on the level of connectivity of the airport. This study aimed to quantify the connectivity between two airports in the national air transportation network. Based on the connectivity data, it can be determined that appropriate mitigation strategies during an airport closure due to force majeure.

Strategic Development of ASEAN Logistics Infrastructure

Introduction:The Association of Southeast Asian Nations (ASEAN) recently launched its ASEAN Economic Community (AEC), which could potentially revolutionize the economic output in the region through free movement of goods, people, and capital across borders. At this stage, several trade barriers still exist which limit successes in AEC.Literature Review:This article assesses strategic opportunities, weaknesses, and threats to trade in the region, with a particular focus on logistics infrastructure. A review and analysis of the quality of land, air, and sea transportation networks is provided.Recommendations and Conclusion:Recommendations are made pertaining to customs and investment policies, security, safety, and infrastructure development. AEC is found capable of achieving its goals given that trade participants have adequate means by which they can deliver their goods.

Social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong

The spread of many respiratory infections is determined by contact patterns between infectious and susceptible individuals in the population. There are no published data for quantifying social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong which is a hotspot for emerging infectious diseases due to its high population density and connectivity in the air transportation network. We adopted a commonly used diary-based design to conduct a social contact survey in Hong Kong in 2015/16 using both paper and online questionnaires. Participants using paper questionnaires reported more contacts and longer contact duration than those using online questionnaires. Participants reported 13 person-hours of contact and 8 contacts per day on average, which decreased over age but increased with household size, years of education and income level. Prolonged and frequent contacts, and contacts at home, school and work were more likely to involve physical contacts. Strong age-assortativity was observed in all age groups. We evaluated the characteristics of social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong. Our findings could help to improve the design of future social contact surveys, parameterize transmission models of respiratory infectious diseases, and inform intervention strategies based on model outputs.

Increasing airline travel may facilitate co-circulation of multiple dengue virus serotypes in Asia.

The incidence of dengue has grown dramatically in recent decades worldwide, especially in Southeast Asia and the Americas with substantial transmission in 2014–2015. Yet the mechanisms underlying the spatio-temporal circulation of dengue virus (DENV) serotypes at large geographical scales remain elusive. Here we investigate the co-circulation in Asia of DENV serotypes 1–3 from 1956 to 2015, using a statistical framework that jointly estimates migration history and quantifies potential predictors of viral spatial diffusion, including socio-economic, air transportation and maritime mobility data. We find that the spread of DENV-1, -2 and -3 lineages in Asia is significantly associated with air traffic. Our analyses suggest the network centrality of air traffic hubs such as Thailand and India contribute to seeding dengue epidemics, whilst China, Cambodia, Indonesia, and Singapore may establish viral diffusion links with multiple countries in Asia. Phylogeographic reconstructions help to explain how growing air transportation networks could influence the dynamics of DENV circulation.

How transfer flights shape the structure of the airline network

In this paper, we analyse the gravity model in the global passenger air-transport network. We show that in the standard form, the model is inadequate for correctly describing the relationship between passenger flows and typical geo-economic variables that characterize connected countries. We propose a model for transfer flights that allows exploitation of these discrepancies in order to discover hidden subflows in the network. We illustrate its usefulness by retrieving the distance coefficient in the gravity model, which is one of the determinants of the globalization process. Finally, we discuss the correctness of the presented approach by comparing the distance coefficient to several well-known economic events.