Relevant bibliographies by topics / Airline network management

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Airline network management'

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Published: 4 June 2021
Last updated: 14 February 2022

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Journal articles on the topic "Airline network management"

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Lu, Jin-Long, and Pei-Ya Siao. "Determining the antecedents and consequences of the airline brand personality." Journal of Airline and Airport Management 9, no. 1 (2019): 1. http://dx.doi.org/10.3926/jairm.121.

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Purpose: This study investigates air passengers’ perceptions of the brand personalities of airlines and explores the relationships between the brand personality and its antecedent factor, the country-of-origin of the airlines, and the consequent factor which is the purchase intentions to the corresponding airlines.Design/methodology/approach: The study uses a questionnaire survey containing air passengers’ trip characteristics and demographics and three main scales: country-of-origin, brand personality, and purchase intentions to collect the data of 490 respondents flying from Kaohsiung to Macao. The passengers are from three types of airlines: an international airline with a global network, a regional airline, and a low-cost carrier. The analysis of variance (ANOVA) was conducted to investigate the differences in the perceptions of brand personalities of airlines and several models were developed to determine the antecedent and the consequent factors of airline brand personality.Findings: The air passengers’ perceptions regarding the brand personalities of different types of airlines were significantly different. The country-of-origin of airlines was proved as a significant factor for the brand personality. The brand personality also significantly influenced passengers’ loyalty to the corresponding airlines. Moreover, some demographic and trip characteristics such as personal monthly income, memberships in the airline’s frequent flyer program, and experiences with the airlines were also determined as the significant variables to impact passengers’ loyalties.Originality/value: The concept of brand personality has been explored by various researches but few related to airline management and identified as a key element to brand marketing. Particularly, low-cost carriers always implement different marketing strategies to create a distinctive position in their target customers’ mind and legacy airlines are also doing different things to retain their customers. Therefore, investigating passengers’ perceptions of airlines from the perspective of brand personality is also an important issue for airline management. Not only does this study prove the differences in passengers’ cognitions of brand personalities of a global network airline, a regional network airline, and a low-cost airline but conclude the determinants and influences of the brand personality.
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Wu, Weiwei, Haoyu Zhang, Shengrun Zhang, and Frank Witlox. "Community Detection in Airline Networks: An Empirical Analysis of American vs. Southwest Airlines." Journal of Advanced Transportation 2019 (December 31, 2019): 1–11. http://dx.doi.org/10.1155/2019/3032015.

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In this paper, we develop a route-traffic-based method for detecting community structures in airline networks. Our model is both an application and an extension of the Clauset-Newman-Moore (CNM) modularity maximization algorithm, in that we apply the CNM algorithm to large airline networks, and take both route distance and passenger volumes into account. Therefore, the relationships between airports are defined not only based on the topological structure of the network but also by a traffic-driven indicator. To illustrate our model, two case studies are presented: American Airlines and Southwest Airlines. Results show that the model is effective in exploring the characteristics of the network connections, including the detection of the most influential nodes and communities on the formation of different network structures. This information is important from an airline operation pattern perspective to identify the vulnerability of networks.
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Zhang, Xu, Ming Zhao, Shi Min Kuang, and Qing Du. "Research on Airline Company Fuel-Saving Model Based on Petri Network." Advanced Materials Research 616-618 (December 2012): 1107–10. http://dx.doi.org/10.4028/www.scientific.net/amr.616-618.1107.

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It has become the primary task of the airlines to pay attention to fuel-efficient, deepening the fuel-efficient process, work to strengthen oil saving management, and construct fuel-efficient system to reduce cost pressure and improve the market competitiveness. This paper, aiming at solving the problems existing in airlines fuel saving and cost control management, analyzes airlines internal main business process. By using Petri nets theory and the top-down method in modeling aviation company fuel-efficient engineering system, this paper, based on Petri nets, builds airlines fuel-efficient models and airline management process with its aim at fuel saving, which provides a visual and effective modeling methods and countermeasures for airlines fuel reduction work.
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Vidović, Andrija, Sanja Steiner, and Igor Štimac. "Development Potentials of Low Cost Aviation in the Republic of Croatia." PROMET - Traffic&Transportation 23, no. 6 (2012): 519–27. http://dx.doi.org/10.7307/ptt.v23i6.187.

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The liberalization of the aviation market has enabled low-cost airlines to take over a significant share in the aviation market. Benefits of low-cost models are multiple, both for passengers and for secondary and regional airports, which were neglected in the past and which record significant inflow of passengers with the arrival of low-cost airlines. In the structure of the air traffic in the Republic of Croatia in the last ten years, there has been a progressive growth of foreign low-cost airline operations, which suggests a potential for the operation of a Croatian low-cost airline. This paper defines the criteria applicable to modelling of a low-cost airline in the Republic of Croatia in the relevant context of fleet management, route networking and operator’s processes in traffic technology. It analyzes the dynamics of low-cost airlines operations in the structure of air traffic in Croatia and the impact of traffic on the status of airports and the national operator. KEY WORDS: low-cost airline, traditional airline, airport, route network, fleet management
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Mhlanga, Oswald, Jacobus Steyn, and John Spencer. "The airline industry in South Africa: drivers of operational efficiency and impacts." Tourism Review 73, no. 3 (2018): 389–400. http://dx.doi.org/10.1108/tr-07-2017-0111.

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Purpose The airline industry is structurally challenged by its very nature, because of high overhead and capital costs. This is further exacerbated by macro-predictability and micro-uncertainty, thereby making it difficult for airlines in South Africa to attain operational efficiency. The purpose of this study is to identify drivers of operational efficiency and their impacts on airline performances in South Africa. Design/methodology/approach An extensive data collection using primary and secondary sources enabled the researchers to gather data on all the airlines operating in South Africa, for the period of 2012-2016, on a variety of parameters. A two-stage empirical analysis was carried out, which involved estimation of operational efficiencies during the first stage by using data envelopment analysis (DEA) and determination of performance drivers during the second stage by using a two-way random-effects generalised least squares regression and also a Tobit model. Findings From the study, it is clear that two structural drivers, namely, “aircraft size” and “seat load factor”, and two executional drivers, namely, “low cost business model” and “revenue hours per aircraft”, significantly impacted (p < 0.05) positively on airline efficiencies in South Africa. To improve efficiency, management should first concentrate on the drivers that can be changed in the short-term (executional drivers) and later focus on the drivers that require long-term planning (structural drivers). However, among the structural drivers, only “aircraft families” had a negative impact on airline efficiencies, whilst among executional drivers, only “block hours” negatively impacted on airline efficiencies. Research limitations/implications Despite the importance of this study, it is not free of limitations. Firstly, because of the small size of the industry, fewer airlines and lack of detailed data, the study could not consider other important factors such as optimal routing and network structure. Secondly, although non-aeronautical revenues have become increasingly important in airline management, they were not included in this study. Further studies may investigate the impact of these factors on airline efficiency. Practical implications The results have potential policy implications. Firstly, as the domestic airline market in South Africa is too small to operate with a smaller aircraft efficiently, airlines that intend to make use of smaller aircraft should first identify niche markets where they can have a route monopoly, such as SA Airlink. Secondly, as block time negatively affected airline efficiency, airlines can undertake schedule adjustments to reduce block time and thus improve technical efficiency. Originality/value This paper is a first attempt to identify drivers of operational efficiency in the airline industry in South Africa. The results indicate that DEA is a useful tool to identify factors impacting airline efficiency and could improve airline performances in South Africa.
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Low, Joyce, and Kum Khiong Yang. "Understanding the operating landscape of the global airline industry: A DEA integrated alternating conditional expectation approach." Journal of Airline and Airport Management 9, no. 2 (2019): 27. http://dx.doi.org/10.3926/jairm.126.

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Purpose: This study investigates the relationships between service efficiency in 5 major cost centres (namely, business orientation, network coverage, physical resources, maintenance, repair and overhaul (MRO), and human resources) and profitability in the global airline industry.Design/methodology/approach: The study integrates the Slack-based Model (SBM) of Data Envelopment Analysis (DEA) with the Alternating Conditional Expectation (ACE) regression to understand the relationships between an airline’s profitability and its efficiencies in 5 identified operations areas.Findings: Based on the observational data obtained from 75 international airlines, the relationships between operational performances and profitability are found to be curvilinear and contingent on an airline’s operating model.Research limitations/implications: The omission of non-IATA airlines and many low cost carriers may hinder a holistic view of the airline industry.Practical implications: Management can influence the profitability of an airline through its strategic operations decisions that affect an airline’s cost, service quality, and financial structure after the influences of location and size have set the stage. Airlines pursuing cost leadership should seek to increase productivity especially in MRO, human resources and physical resources; whereas airlines pursuing service differentiation may choose to provide quality service at lower efficiencies or pursue an approach to improve quality and efficiencies simultaneously.Originality/value: Identifying operations practices that are consistent with a firm’s competitive priorities is important in the multifaceted service environment today. An integrated SBM-ACE regression model, which permits different input-output mix, variable return to scale and non-linear relationship, is proposed and applied to analyze the profit impact of service efficiencies in the five key operations areas.
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Jin, Ying, Ye Wei, Chunliang Xiu, Wei Song, and Kaixian Yang. "Study on Structural Characteristics of China’s Passenger Airline Network Based on Network Motifs Analysis." Sustainability 11, no. 9 (2019): 2484. http://dx.doi.org/10.3390/su11092484.

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The air passenger transport network system is an important agent of social and economic connections between cities. Studying on the airline network structure and providing optimization strategies can improve the airline industry sustainability evolution. As basic building blocks of broad networks, the concept of network motifs is cited in this paper to apply to the structural characteristic analysis of the passenger airline network. The ENUMERATE SUBGRAPHS (G, k) algorithm is used to identify the motifs and anti-motifs of the passenger airline network in China. A total of 37 airline companies are subjected to motif identification and exploring the structural and functional characteristics of the airline networks corresponding to different motifs. These 37 airline companies are classified according to the motif concentration curves into three development stages, which include mono-centric divergence companies at the low-level development stage, transitional companies at the intermediate development stage, and multi-centric and hierarchical companies at the advanced development stage. Finally, we found that adjusting the number of proper network motifs is useful to optimize the overall structure of airline networks, which is profitable for air transport sustainable development.
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Lederer, Phillip J., and Ramakrishnan S. Nambimadom. "Airline Network Design." Operations Research 46, no. 6 (1998): 785–804. http://dx.doi.org/10.1287/opre.46.6.785.

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You, Peng-Sheng. "Airline seat management with round-trip requests." Yugoslav Journal of Operations Research 14, no. 2 (2004): 155–70. http://dx.doi.org/10.2298/yjor0402155y.

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Consider a multi-period multi-fare class airline booking problem related to a two-leg airline network. Travel requests include outbound, inbound trip, and round trips. The round-trip refers to a journey comprising both outbound and inbound trips. To develop a dynamic-nested booking decision-making system for the airline network, this study designs a dynamic model that enables the airline reservations system to devise a set of dynamic decision rules for any given booking status. The booking process is found to be controlled by some set of booking thresholds.
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Bahadir, Cuneyt, and Adem Karahoca. "Airline revenue management via data mining." Global Journal of Information Technology: Emerging Technologies 7, no. 3 (2017): 128–48. http://dx.doi.org/10.18844/gjit.v7i3.2834.

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Revenue maximisation has been of paramount interest in the airline industry during the past few decades, and numerous studies have been reported, aiming at robust analyses. Principal analysis techniques in most of these studies include computational-based prediction algorithms that are used for a given dataset. In this study, airline specific data, which consists of cabin class passenger data, cabin class supplied capacity data, distance of flights, season, year –month data and revenue data, are analysed using various prediction algorithms. Consistencies and accuracies of different algorithms are compared and reported.Keywords: Airline industry, airline revenue data, prediction algorithms, Weka, Bayesian network, sequential minimaloptimisation, support vector machines, multilayer perceptron, radial basis function network.
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Dissertations / Theses on the topic "Airline network management"

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Bratu, Stephane (Stephane J.-C) 1970. "Network value concept in airline revenue management." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/9939.

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Pearson, James. "The competitive strength of Asian network airlines in competing with low-cost carriers and the use of low-cost subsidiaries." Thesis, Loughborough University, 2016. https://dspace.lboro.ac.uk/2134/21847.

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While 3.3 billion people flew worldwide in 2014 a large number of these were from developed countries. It is emerging countries which offer the greatest potential for future air traffic growth, with forecasts suggesting that 7.3 billion people will fly by 2034. The greatest proportion of this traffic will be in the Asia-Pacific region where there is already high low-cost carrier penetration. Given increasing price-based competition within short-haul markets, there are many significant challenges in terms of how Asian network airlines respond to LCC competition, and a popular response is the use of low-cost subsidiaries. Thus, the aims of this research are to establish the sources of competitive advantage of Asian airlines generally, and to examine the competitive responses of Asian network airlines and the strategic capabilities of them in competing with low-cost carriers, with a particular focus upon the use of low-cost subsidiaries. This research is underpinned with competitive advantage theory, particularly the resource-based view which concerns the internal environment of firms where each firm possesses a collection of unique resources and capabilities that provide the foundation for competitive strategy. For this research, data were collected from 49 senior airline management personnel using questionnaire surveys, resource surveys, and semi-structured interviews. The data were then analysed using VRIN analysis, the importance and difficulty of 37 competitive responses, strategic capability analysis, and the product and organisational architecture model. The results found that both a strong strategy and stable leadership are crucial. The strategies of Asian network airlines must be flexible to respond appropriately to competitive threats as they materialise, with this responsiveness contributing to the attainment of competitive advantage. Out of an analysed 36 intangible resources, the top resources for competitive advantage and responding to competitive threats for Asian airlines generally are slots, brand, and product and service reputation, with the importance of these based more on being hard to copy than valuable. Each analysed airline business model has a relatively distinct core bundle of intangible resources which explains the internal sources of their competitive advantage. The need for Asian network airlines to strengthen their competitive advantage and their ability to compete is because low-cost carriers impact them in many ways, most notably through a reduction in market share and reduced yields given the key motivation of customers within short-haul markets and economy class is now price and value-for-money. Asian network airlines are most likely to respond to low-cost carriers if they focus upon their core markets, grow their market share, and target the core higher-yielding passengers on which network airlines rely. In such instances, Asian network airlines should respond by focusing more on their brands and meeting the needs of their core targeted market segments. There is a strong positive correlation between profit margin and the strategic capability to compete with low-cost carriers. Yet, Asian network airlines have relatively weak capabilities overall. While Vietnam Airlines, Malaysia Airlines, and Garuda Indonesia are reasonably well placed to compete, network airlines from Northeast Asia, in particular, must strengthen their capabilities especially as Japan, China, and Taiwan are witnessing fast low-cost carrier growth. However, the possession of a strong capability does not mean it is fully or properly leveraged. To compete more effectively with low-cost carriers, the most important competitive responses, based upon analysis of 37 responses, are the ability of management to quickly introduce changes, leveraging brand strength, and increasing aircraft utilisation. Based on the relationship between the importance and difficulty of responses, the most crucial responses for competitive advantage of Asian network airlines are reducing costs to within 30% of LCCs and increasing aircraft utilisation. If achieved, these should lead to meaningful sustained advantage. Low-cost subsidiaries are easier to implement than for network airlines to significantly reduce costs, change to one fleet, or reduce the use of direct distribution, which may explain their popularity within Asia and them being a borderline very essential competitive response. For network airlines, low-cost subsidiaries are a more effective way to compete with low-cost carriers, to participate in the growth of the budget segment, a means of operating uneconomic routes, and to remove unprofitable customers. Network airlines can then focus upon their core market segments and their core competencies. However, their creation is reactive and not proactive which undermines their effectiveness, likewise that low-cost subsidiaries suffer from poor profitability, higher costs, and much smaller size and scale than their key low-cost competitors. This research recommends that Asian network airlines strengthen their existing and primary sources of competitive advantage while pursuing new sources of advantage. While the strategic capabilities of Asian network airlines have strengthened over time, it is essential that they are further strengthened and fully acted upon given increasing competitiveness. The use of low-cost subsidiaries will continue, but it is crucial for themselves and their parent network airlines that they improve their ability to compete and thereby their performance.
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Chi, Zhihang. "Airline yield management in a dynamic network environment." Thesis, Massachusetts Institute of Technology, 1995. http://hdl.handle.net/1721.1/11735.

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Joshi, Kapil. "Modeling alternate strategies for airline revenue management." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000557.

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Cetiner, Demet. "A Risk-sensitive Approach For Airline Network Revenue Management Problems." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608920/index.pdf.

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In this thesis, airline network revenue management problem is considered for the case with no cancellations and overbooking. In literature, there exist several approximate probabilistic and deterministic mathematical models developed in order to maximize expected revenue at the end of the reservation period. The aim of this study is to develop models considering also the risks involved in the proposed booking control policies. Two linear programming models are proposed which incorporate the variance of the revenue. The objective of the models is to effectively balance the tradeoff between the expectation and variance of the revenue. The performances of the proposed models are compared to the previous models through a numerical study. The seat allocations resulting from the mathematical models are used in a simulation model working with several booking control policies. The probability distributions of the revenues are investigated and the revenues are compared in terms of expectation, standard deviation, coefficient of variation and probability of poor performance. It is observed that the use of the proposed models decreases the variability of the revenue and thereby the risk of probability of poor performance. Also, the expected revenues obtained by implementing the solutions of the proposed models with nested booking control policies turn out to be higher than other probabilistic models as long as the degree of variance incorporation is within some interval. When compared with the deterministic models, the proposed models provides for the decision makers with alternative, preferable policies in terms of the expectation and the variability measures.
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Mohan, Baskar. "Integrated pricing and seat allocation for airline network revenue management." [Tampa, Fla.] : University of South Florida, 2005. http://purl.fcla.edu/fcla/etd/SFE0001267.

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Zickus, Jeffrey S. (Jeffrey Stuart) 1973. "Forecasting for airline network revenue management : revenue and competitive impacts." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/10103.

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Mohan, Baskar. "Integrated Pricing and Seat Allowance for Airline Network Revenue Management." Scholar Commons, 2005. https://scholarcommons.usf.edu/etd/776.

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The airline industry is facing unprecedented challenges in generating sufficient revenues to stay in business. Airlines must capture the greatest revenue yield from every flight by leaving no seats unsold and not over filling the cabin with discount fares. To succeed in doing the above airlines must be able to accurately forecast each of their market segments, manage product andprice availability to maximize revenue and react quickly to competitive changes in the market place. Thus seat inventory control and ticket pricing form the two major tools of revenue management. The focus of this paper is to consolidate the ideas of seats inventory control and pricing in order to maximize the revenues generated by an airline network. A continuous time yield management model for a network with multiple legs, multiple fare classes and dynamic price changes for all fare classes is considered. Each fare class has a set of fares from which the optimal fare is chosen based upon the Minimum Acceptable Fare (MAF) which performs the critical role in the decision process. A machine Learning based algorithm, EMSRa based and EMSRb based algorithm for obtaining dynamic policies for combined pricing and allocation. The algorithms are implemented for a sample network with eight cities, eleven logs, thirty origin-destinations(ODs), three fare classes, three levels of fares in each class and ninety itineraries.
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Hou, Yanting. "Airline network revenue management : integrated optimization of hub location and capacity allocation." Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLE030.

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La gestion des revenus d’un réseau de compagnies aériennes, un des problèmes le plus critiques dans le secteur du transport aérien, a reçu une attention significative depuis ces dernière décennies. Cependant, de nombreuses problématiques doivent encore être traitées. Cette thèse étudie quatre nouveaux problèmes de la gestion des revenus dans un réseau de compagnies aériennes. D'abord, un problème de dimensionnement de capacité du réseau avec alliances concurrentes est étudié. Dans ce problème, les concurrences horizontales et verticales sont considérées et la demande est supposée déterministe. L’objectif est de maximiser les revenus globaux de l’alliance en déterminant la capacité (en nombre de places) dans les vols pour chaque classe tarifaire de chaque compagnie. Le problème est formulé en programmation linéaire en nombres entiers et résolu à l’aide du solveur CPLEX. Deuxièmement, un problème intégrant la localisation de p-hub médian et le dimensionnement des capacités (places) est étudié pour maximiser une combinaison du bénéfice moyen et du bénéfice au pire cas. Pour ce problème, un seul hub à capacité illimitée est considéré. De plus, les incertitudes sur la demande sont représentées à l’aide d’un ensemble fini des scénarios. Le problème est formulé en programmation stochastique à deux étapes. Ensuite, un algorithme génétique (GA) est proposé pour résoudre le problème pour chaque scénario. Les résultats numériques montrent que la méthode est meilleure que celles dans la littérature qui considèrent uniquement le bénéfice moyen. Le troisième problème étudié est une extension naturelle du deuxième dans lequel la capacité de hub à localiser est limitée et les perturbations qui peuvent impacter la capacité du hub, telles que des conditions météorologiques, sont prises en compte. Deux formulations du problème sont proposées : (1) une programmation stochastique à deux étapes sur la base des scénarios, et (2) optimisation hybride de programmation stochastique à deux étapes à l’aide de pondération. Ensuite, l’approximation moyenne par échantillonnage (SAA) et le GA sont appliqués pour résoudre le problème, respectivement. Les résultats numériques montrent que la SAA est plus performante que le GA. Le quatrième problème est aussi une extension du deuxième problème où la compagnie aérienne doit respecter le niveau d'émissions de CO2 imposé. Le problème est modélisé en programmation stochastique à deux étapes sur la base des scénarios. De plus, une méthode SAA est proposée pour sa résolution<br>As one of critical problems in aviation industry, airline network revenue management has received significant attention in recent decades. However, many issues still need to be addressed. This thesis investigates four new airline network revenue management problems. Firstly, a network capacity allocation problem with competitive alliances is studied. In this problem, horizontal and vertical competitions and deterministic demand are considered. The aim is to maximize the global alliance revenue by determining the (seat) capacities in flights for each fare class of each airline. The problem is formulated into a mixed integer programming and is solved by a commercial solver CPLEX. Secondly, an integrated p-hub median location and (seat) capacity allocation problem is investigated to maximize the combined average-case and worst-case profits of an airline. For this problem, an uncapacitated hub is considered and uncertain demand is represented by a finite set of scenarios. The studied problem is formulated based on a two-stage stochastic programming framework. Then a Genetic Algorithm (GA) is proposed to solve the problem for each scenario. Computational results show that the proposed method outperforms those in the literature only considering average-case profit. The third studied problem is a generalization of the second one in which the capacity of hub to be located is limited and disruptions which can impact airline hub capacity, such as adverse weather, are considered. Two formulations of the problem are proposed based on : (1) a scenario-based two-stage stochastic programming, and (2) a weight-based hybrid two-stage stochastic programming-robust optimization framework. Then a Sample Average Approximation (SAA) method and a GA are applied to solve them, respectively. Computational results show that the SAA is more effective than the GA. The fourth problem is also an extension of the second one where an airline is subjected to a CO2 emission limit. The problem is modeled into a scenario-based two-stage stochastic programming. And a SAA method is proposed to solve it
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Greiser, Henning. "The impacts of major airline mergers on network consolidation and traffic performance." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/81072.

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Thesis (S.M. in Management Studies)--Massachusetts Institute of Technology, Sloan School of Management, 2013.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 114-116).<br>In response to the many challenges faced by US airlines in the past decade, merger activity has increased significantly. By combining their networks, airlines commonly aim to not only realize cost synergies but also achieve revenue synergies as well through increased network coverage. In practical terms, this means that the combined airline can cut its total capacity without reducing traffic as it benefits from a larger network and more connecting options via its hubs. The objective of this thesis is to find evidence to confirm this effect based on recent merger activity by comparing both capacity and traffic data before and after the integration period. Particular emphasis is placed on the changing role of hubs to highlight capacity and traffic shifts in a combined network. Two of the most recent major mergers, Delta-Northwest and United-Continental, exhibit how the networks of previously independent carriers were consolidated to achieve the above-mentioned synergies. Delta concentrated capacity at its largest hub in Atlanta and a small number of additional hubs while other hubs experienced a significant downsizing. Additionally, the airline also eliminated a large number of point-to-point services that were bypassing the hubs in order to maximize the use of its hubs. United and Continental, on the other hand, engaged in fairly minor capacity redistribution instead of sweeping reductions. Both carriers increased the share of capacity operated by regional partners and grew capacity between most of the hubs as well. Over the same time frame, however, both of the combined airlines lost passengers compared to their pre-merger levels. While exogenous factors like the recent recession and operational issues played a role, network strategies at both airlines also affected traffic. Delta was unable to recover most of the passengers it lost on the eliminated point-to-point services. For United, the shift towards more international capacity indicates a displacement of domestic traffic by international connecting passengers. Although both carriers had not returned to their pre-merger traffic levels by the end of the integration period, Delta's 2012 performance suggests that network integration and consolidation can have positive effects in the long run.<br>by Henning Greiser.<br>S.M.in Management Studies
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Books on the topic "Airline network management"

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Airline operations and delay management: Insights from airline economics, networks, and strategic schedule planning. Ashgate, 2010.

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Wu, Cheng-Lung. Airline operations and delay management: Insights from airline economics, networks, and strategic schedule planning. Ashgate, 2009.

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Kleymann, Birgit. The Development of multilateral alliances: The case of the airline industry. Helsinski School of Economics, 2002.

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Abdelghany, Ahmed, and Khaled Abdelghany. Airline Network Planning and Scheduling. Wiley, 2018.

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Abdelghany, Ahmed, and Khaled Abdelghany. Airline Network Planning and Scheduling. Wiley & Sons, Incorporated, John, 2018.

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Discrete Choice Models for Airline Network Management. Schulz-Kirchner, Idstein, 2002.

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Burghouwt, Guillaume. Airline Network Development in Europe and Its Implications for Airport Planning (Ashgate Studies in Aviation Economics and Management) (Ashgate Studies in Aviation Economics & Management). Ashgate Pub Co, 2007.

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Air Transport Networks: Theory and Policy Implications (Transport Economics, Management and Policy series). Edward Elgar Publishing, 2000.

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Book chapters on the topic "Airline network management"

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Bieger, Thomas, and Andreas Wittmer. "Airline Strategy: From Network Management to Business Models." In Aviation Systems. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20080-9_5.

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Sun, Xiaoyun Sherry, Erik Brauner, and Sharon Hormby. "A Large-Scale Neural Network for Airline Forecasting in Revenue Management." In Operations Research in the Airline Industry. Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5501-8_2.

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Sarvari, Peiman Alipour, and Fethi Calisir. "Evaluating Airline Network Robustness Using Relative Total Cost Indices." In Lecture Notes in Management and Industrial Engineering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71225-3_5.

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Han, Lie, and Ning Zhang. "P-Hub Airline Network Design Incorporating Interaction Between Elastic Demand and Network Structure." In Emerging Technologies for Information Systems, Computing, and Management. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7010-6_11.

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Gaul, Wolfgang, and Christoph Winkler. "Aviation Data Analysis by Linear Programming in Airline Network Revenue Management." In Studies in Classification, Data Analysis, and Knowledge Organization. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-25147-5_1.

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Pan, Fu-bin, Zhi-sang Dai, Xiao-dan Gong, and Jun-yi Wu. "The Optimization Model of Airline Network on the Basis of Hub-and-Spoke." In International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012) Proceedings. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38445-5_135.

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Lu, Wen-Min, Shiu-Wan Hung, Qian Long Kweh, Wei-Kang Wang, and En-Tzu Lu. "Production and Marketing Efficiencies of the U.S. Airline Industry: A Two-Stage Network DEA Approach." In International Series in Operations Research & Management Science. Springer US, 2014. http://dx.doi.org/10.1007/978-1-4899-8068-7_21.

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Aubakirova, Damira, and Natalia Konovalova. "Management of Financial Stability in Airlines: Problems and Solutions." In Lecture Notes in Networks and Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44610-9_56.

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Alomar, Iyad, and Adilkhan Zamanbek. "Risks Associated with Changes in Management Staff in the Airline. Kazakhstan Case Study." In Lecture Notes in Networks and Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68476-1_26.

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Hu, Xiao-Bing, and Ezequiel Di Paolo. "A Genetic Algorithm Based on Complex Networks Theory for the Management of Airline Route Networks." In Nature Inspired Cooperative Strategies for Optimization (NICSO 2007). Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-78987-1_45.

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Conference papers on the topic "Airline network management"

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Dong, Bing, Wen Du, and Lianming Zhao. "Airline Network Revenue Management Based on Simulated Annealing Genetic Algorithm." In International Conference of Logistics Engineering and Management (ICLEM) 2010. American Society of Civil Engineers, 2010. http://dx.doi.org/10.1061/41139(387)391.

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Hall, W. D., and E. H. Peterson. "ASCENT: a network-wide simulation of air traffic flow management incorporating airline decisions." In Proceedings of 2002 American Control Conference. IEEE, 2002. http://dx.doi.org/10.1109/acc.2002.1023203.

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DePold, Hans R., and F. Douglas Gass. "The Application of Expert Systems and Neural Networks to Gas Turbine Prognostics and Diagnostics." In ASME 1998 International Gas Turbine and Aeroengine Congress and Exhibition. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/98-gt-101.

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Abstract:
Condition monitoring of engine gas generators plays an essential role in airline fleet management. Adaptive diagnostic systems are becoming available that interpret measured data, furnish diagnosis of problems, provide a prognosis of engine health for planning purposes, and rank engines for scheduled maintenance. More than four hundred operations worldwide currently use versions of the first or second generation diagnostic tools. Development of a third generation system is underway which will provide additional system enhancements and combine the functions of the existing tools. Proposed enhancements include the use of artificial intelligence to automate, improve the quality of the analysis, provide timely alerts, and the use of an Internet link for collaboration. One objective of these enhancements is to have the intelligent system do more of the analysis and decision making, while continuing to support the depth of analysis currently available at experienced operations. This paper presents recent developments in technology and strategies in engine condition monitoring including: 1) application of statistical analysis and artificial neural network filters to improve data quality; 2) neural networks for trend change detection, and classification to diagnose performance change; and 3) expert systems to diagnose, provide alerts and to rank maintenance action recommendations.
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Li, Depeng, and Rui Zhang. "A framework to mitigate airliner risk in air traffic management." In 2016 IEEE Conference on Communications and Network Security (CNS). IEEE, 2016. http://dx.doi.org/10.1109/cns.2016.7860500.

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Teymourian, Ehsan, Ali Sadeghi, and Farzin Taghipourian. "A dynamic virtual hub location problem in airline networks - formulation and metaheuristic solution approaches." In 2011 IEEE International Technology Management Conference (ITMC). IEEE, 2011. http://dx.doi.org/10.1109/itmc.2011.5996004.

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Liping Xu and Jinlin Li. "A model of capacity control with overbooking for a two-leg airlines network." In 2008 International Conference on Service Systems and Service Management (ICSSSM 2008). IEEE, 2008. http://dx.doi.org/10.1109/icsssm.2008.4598477.

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Ding, Songbin, and Yi Ru. "Flight risk assessment to airlines using Bayesian belief networks and fuzzy comprehensive evaluation." In 2008 IEEE International Conference on Industrial Engineering and Engineering Management. IEEE, 2008. http://dx.doi.org/10.1109/ieem.2008.4738076.

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Xu, Lei, Qing Zhang, and Xiao-Ning Guo. "A duopolistic framework for ancillary service strategies of dual airlines." In AADNIC-ABMECR 2020: The 2nd Africa-Asia Dialogue Network International Conference on Advances in Business Management and Electronic Commerce Research. ACM, 2020. http://dx.doi.org/10.1145/3440094.3440924.

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