Pub Date : 2025-12-19DOI: 10.1016/j.jairtraman.2025.102951
Felix Müller , Alexander Barke , Olof Nittinger , Thomas S. Spengler
Technological advancements foster the development of novel aircraft concepts such as electric vertical take-off and landing aircraft (eVTOLs). As a result of their promised operational benefits, such as low-emission operations and travel time savings, eVTOLs have the potential to complement or substitute existing ground transportation modes. However, their market penetration predominantly depends on economically viable operation. A widely used indicator for evaluating economic performance in aviation is the Direct Operating Cost (DOC). Currently, there is only limited public documentation on methodologies for estimating DOC of eVTOLs, and existing approaches are often abstract. Therefore, this article introduces the DOCeV, a model for estimating eVTOL DOC. The model is based on a reference methodology for conventional aircraft but is modified and extended to address the specific characteristics of (future) eVTOL operations. The DOCeV enables the estimation of costs associated with ownership, insurance, crew, energy, fees, and maintenance. Additionally, an eVTOL performance analysis is conducted within the model, the annual eVTOL utilisation is estimated, and an indicative ticket pricing approach is provided. The DOCeV has been implemented in a tool and validated using an input data set developed for a regional airport shuttle case study between Munich, Germany, and Salzburg, Austria. When applying the DOCeV, the DOC estimates for shorter, regional operations align well with existing literature. Estimates for longer missions are slightly higher than those reported in the literature. Overall, the DOCeV is considered a comprehensive and promising model for estimating realistic eVTOL DOC.
{"title":"DOCeV: A New Holistic Model for Direct Operating Cost Estimation of Electric Vertical Take-Off and Landing Aircraft","authors":"Felix Müller , Alexander Barke , Olof Nittinger , Thomas S. Spengler","doi":"10.1016/j.jairtraman.2025.102951","DOIUrl":"10.1016/j.jairtraman.2025.102951","url":null,"abstract":"<div><div>Technological advancements foster the development of novel aircraft concepts such as electric vertical take-off and landing aircraft (eVTOLs). As a result of their promised operational benefits, such as low-emission operations and travel time savings, eVTOLs have the potential to complement or substitute existing ground transportation modes. However, their market penetration predominantly depends on economically viable operation. A widely used indicator for evaluating economic performance in aviation is the Direct Operating Cost (DOC). Currently, there is only limited public documentation on methodologies for estimating DOC of eVTOLs, and existing approaches are often abstract. Therefore, this article introduces the DOCeV, a model for estimating eVTOL DOC. The model is based on a reference methodology for conventional aircraft but is modified and extended to address the specific characteristics of (future) eVTOL operations. The DOCeV enables the estimation of costs associated with ownership, insurance, crew, energy, fees, and maintenance. Additionally, an eVTOL performance analysis is conducted within the model, the annual eVTOL utilisation is estimated, and an indicative ticket pricing approach is provided. The DOCeV has been implemented in a tool and validated using an input data set developed for a regional airport shuttle case study between Munich, Germany, and Salzburg, Austria. When applying the DOCeV, the DOC estimates for shorter, regional operations align well with existing literature. Estimates for longer missions are slightly higher than those reported in the literature. Overall, the DOCeV is considered a comprehensive and promising model for estimating realistic eVTOL DOC.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102951"},"PeriodicalIF":3.6,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145786751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-19DOI: 10.1016/j.jairtraman.2025.102957
Jiayu Liu , Ningning Nicole Kong , Yi Gao
This study employs a Difference-in-Differences (DiD) to measure the land use change after a new airport terminal was being built. By comparing land use changes around airports with newly constructed terminals to those around airports without terminal expansion, the study isolates the effects of terminal developments on urban growth and land transformation. Land use data from the United States National Land Cover Database (NLCD) was analyzed across two treatment periods (2011 and 2016) to evaluate shifts in different land use categories such as developed, agricultural, and natural land. Findings indicate that new terminals construction is usually accompanied by accelerating urbanization, with high-intensity developments expanding at the expense of natural and agricultural lands. An exception appears in the 2011 treatment cohort, where agricultural land increasing stands out, likely reflecting concurrent regional conservation and restoration initiatives.
{"title":"Assessing spatial development footprint of urban areas surrounding new airport terminal infrastructure","authors":"Jiayu Liu , Ningning Nicole Kong , Yi Gao","doi":"10.1016/j.jairtraman.2025.102957","DOIUrl":"10.1016/j.jairtraman.2025.102957","url":null,"abstract":"<div><div>This study employs a Difference-in-Differences (DiD) to measure the land use change after a new airport terminal was being built. By comparing land use changes around airports with newly constructed terminals to those around airports without terminal expansion, the study isolates the effects of terminal developments on urban growth and land transformation. Land use data from the United States National Land Cover Database (NLCD) was analyzed across two treatment periods (2011 and 2016) to evaluate shifts in different land use categories such as developed, agricultural, and natural land. Findings indicate that new terminals construction is usually accompanied by accelerating urbanization, with high-intensity developments expanding at the expense of natural and agricultural lands. An exception appears in the 2011 treatment cohort, where agricultural land increasing stands out, likely reflecting concurrent regional conservation and restoration initiatives.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102957"},"PeriodicalIF":3.6,"publicationDate":"2025-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145786754","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-18DOI: 10.1016/j.jairtraman.2025.102956
Wilmar Calderón-Guevara, Mauricio Sánchez-Silva
The critical importance of intergenerational responsibility has placed sustainable infrastructure development at the forefront of global attention, demanding designs that are highly efficient and adaptable to uncertain demands. To address this need, this article proposes and implements a novel methodology to incorporate flexibility into infrastructure system management, enabling dynamic evaluation of system performance and allowing decision-makers to determine the optimal intervention policy. The framework uses stochastic programming to evaluate a set of management policies across multiple scenarios, thereby defining an optimal, robust planning strategy for an airport system. The methodology was successfully validated through a case study of Colombia’s three primary airports (Bogotá, Medellín, and Cali), demonstrating its practical applicability. Key results indicate that the system should prioritize investments in gate facilities, and the selected policy provides a planning guide that ensures positive returns across the entire network. Finally, the study identifies two critical areas for future work: enhancing runway efficiency through network-wide scheduling and applying this framework to other case studies to maximize investments in infrastructure networks.
{"title":"Flexible planning of dynamic airport infrastructure networks","authors":"Wilmar Calderón-Guevara, Mauricio Sánchez-Silva","doi":"10.1016/j.jairtraman.2025.102956","DOIUrl":"10.1016/j.jairtraman.2025.102956","url":null,"abstract":"<div><div>The critical importance of intergenerational responsibility has placed sustainable infrastructure development at the forefront of global attention, demanding designs that are highly efficient and adaptable to uncertain demands. To address this need, this article proposes and implements a novel methodology to incorporate flexibility into infrastructure system management, enabling dynamic evaluation of system performance and allowing decision-makers to determine the optimal intervention policy. The framework uses stochastic programming to evaluate a set of management policies across multiple scenarios, thereby defining an optimal, robust planning strategy for an airport system. The methodology was successfully validated through a case study of Colombia’s three primary airports (Bogotá, Medellín, and Cali), demonstrating its practical applicability. Key results indicate that the system should prioritize investments in gate facilities, and the selected policy provides a planning guide that ensures positive returns across the entire network. Finally, the study identifies two critical areas for future work: enhancing runway efficiency through network-wide scheduling and applying this framework to other case studies to maximize investments in infrastructure networks.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102956"},"PeriodicalIF":3.6,"publicationDate":"2025-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145786752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Airlines increasingly adopt one-brand, multi-AOC (OB-MA) strategies – operating multiple Air Operator Certificates (AOCs) under a single brand identity. Despite their growing prevalence, the strategic rationale and contextual factors driving OB-MA strategy adoption remain underexplored in the academic literature.
This study develops a structured framework for assessing the situational factors that shape the establishment and implementation of OB-MA strategies. Using the Analytic Hierarchy Process (AHP), we identify, classify, and rank 15 key criteria and sub-criteria. Our findings reveal that jurisdictional constraints, strategic trajectory, and organisational lifecycle status are central to the rationale for OB-MA implementation.
This study introduces a distinction between ex-ante qualification criteria – which justify the initial need for OB-MA structures – and ex-post success criteria – which determine their long-term viability. This distinction enhances the practical relevance of the framework, equipping airline executives with a diagnostic tool to assess both the necessity and sustainability of OB-MA strategies in dynamic market environments.
This research offers both theoretical background and practical guidance for OB-MA strategy development and contributes to a more systemic understanding of multi-AOC structures within airline strategy.
{"title":"Beyond the brand: Analysing the rationale and relevance of one-brand, multi-AOC strategies in global airline groups","authors":"Lars-Michael Wendel , Sascha Albers , Wouter Dewulf","doi":"10.1016/j.jairtraman.2025.102952","DOIUrl":"10.1016/j.jairtraman.2025.102952","url":null,"abstract":"<div><div>Airlines increasingly adopt one-brand, multi-AOC (OB-MA) strategies – operating multiple Air Operator Certificates (AOCs) under a single brand identity. Despite their growing prevalence, the strategic rationale and contextual factors driving OB-MA strategy adoption remain underexplored in the academic literature.</div><div>This study develops a structured framework for assessing the situational factors that shape the establishment and implementation of OB-MA strategies. Using the Analytic Hierarchy Process (AHP), we identify, classify, and rank 15 key criteria and sub-criteria. Our findings reveal that jurisdictional constraints, strategic trajectory, and organisational lifecycle status are central to the rationale for OB-MA implementation.</div><div>This study introduces a distinction between ex-ante qualification criteria – which justify the initial need for OB-MA structures – and ex-post success criteria – which determine their long-term viability. This distinction enhances the practical relevance of the framework, equipping airline executives with a diagnostic tool to assess both the necessity and sustainability of OB-MA strategies in dynamic market environments.</div><div>This research offers both theoretical background and practical guidance for OB-MA strategy development and contributes to a more systemic understanding of multi-AOC structures within airline strategy.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102952"},"PeriodicalIF":3.6,"publicationDate":"2025-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145786931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-10DOI: 10.1016/j.jairtraman.2025.102937
Nicolò Avogadro, Chiara Morlotti, Renato Redondi
Demand forecasting is a pivotal aspect of the multifaceted business of airlines and airports, significantly influencing long-term strategic decisions. For airports, accurate traffic forecasts are particularly crucial for aligning infrastructure capacity with future needs, necessitating tailored approaches to capture complex demand dynamics. This paper proposes a novel modeling framework to formulate high-granular itinerary-level demand forecasts, ultimately ensuring robust system-level predictions. The modeling framework leverages a state-of-the-art integrated demand modeling coupled with a customized scenario analysis tool. We demonstrate the validity of the proposed approach in supporting airport strategic planning by reporting the outcomes of its application on the Italian airport system, formulating traffic forecasts up to 2035 and testing predictive ability based on actual traffic data for 2024. We showcase the adaptability of the framework in addressing diverse challenges that decision-makers and policymakers will face in the near future, such as implementing policies to support the aviation industry’s transition to net-zero emissions.
{"title":"Forecasting high-granular air passenger demand flows: An integrated modeling framework applied to the Italian airport system","authors":"Nicolò Avogadro, Chiara Morlotti, Renato Redondi","doi":"10.1016/j.jairtraman.2025.102937","DOIUrl":"10.1016/j.jairtraman.2025.102937","url":null,"abstract":"<div><div>Demand forecasting is a pivotal aspect of the multifaceted business of airlines and airports, significantly influencing long-term strategic decisions. For airports, accurate traffic forecasts are particularly crucial for aligning infrastructure capacity with future needs, necessitating tailored approaches to capture complex demand dynamics. This paper proposes a novel modeling framework to formulate high-granular itinerary-level demand forecasts, ultimately ensuring robust system-level predictions. The modeling framework leverages a state-of-the-art integrated demand modeling coupled with a customized scenario analysis tool. We demonstrate the validity of the proposed approach in supporting airport strategic planning by reporting the outcomes of its application on the Italian airport system, formulating traffic forecasts up to 2035 and testing predictive ability based on actual traffic data for 2024. We showcase the adaptability of the framework in addressing diverse challenges that decision-makers and policymakers will face in the near future, such as implementing policies to support the aviation industry’s transition to net-zero emissions.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102937"},"PeriodicalIF":3.6,"publicationDate":"2025-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145734007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-09DOI: 10.1016/j.jairtraman.2025.102954
Ukbe Üsame Uçar
Aircraft emissions during taxi-out operations constitute a significant portion of local air pollution at airports and are rarely modeled in conjunction with operational and meteorological variables. Although numerous studies focus on fuel burn or emission factors based on the ICAO LTO cycle, limited research integrates real-world airport conditions. In this article, CO2, NOx, CO, and HC emissions during the taxi-out phase at Istanbul Airport for the period 2024–2030 were estimated by considering the technical specifications of aircraft, operational delays, and meteorological visibility indices. Detailed analyses were conducted under three categories (Best, Normal, Worst) and 12 scenarios, and the daily intensity of emissions per unit area was evaluated according to the IDLH health risk indicator. In the estimation study, a new hybrid method called the FoREC-HHO algorithm was developed and compared with machine learning, metaheuristic algorithms, and statistical techniques. As a result of the analysis, the FoREC-HHO algorithm showed the highest accuracy rate for all emission types and achieved the lowest MAE values, demonstrating superior prediction performance. According to the analysis findings, in the worst-case scenario, CO2 emissions increased by 80 %, NOx by 76 %, HC by 78 %, and CO by 66 % between 2024 and 2030. In the normal scenario, the emission increases were observed as 57 % for CO2, 52 % for NOx, 53 % for HC, and 46 % for CO. In contrast, under the best-case scenario, these increases were considerably more moderate, measured at 34 % for CO2, 31 % for NOx, 30 % for HC, and 26 % for CO. In addition, by 2030, the risk density for CO2 is projected to reach 2.33 kg/m2/day, while for CO, this value is 0.01293 kg/m2/day. The calculated densities for NOx and HC were determined to be 0.00221 and 0.00030 kg/m2/day, respectively. These values were found to potentially pose high acute toxicity risks for CO, chronic respiratory and nervous system risks for NOx and HC, and climate-related effects and physiological burdens on personnel working in enclosed spaces for CO2. In this study, a comprehensive approach was presented for both temporal and seasonal estimation of emissions associated with the taxi-out process at airports and health-based risk assessment using the newly developed FoREC-HHO algorithm.
{"title":"Estimation of key pollutant emission during the taxi-out phase using a novel hybrid forecasting algorithm(FoREC-HHO): Application to Istanbul Airport","authors":"Ukbe Üsame Uçar","doi":"10.1016/j.jairtraman.2025.102954","DOIUrl":"10.1016/j.jairtraman.2025.102954","url":null,"abstract":"<div><div>Aircraft emissions during taxi-out operations constitute a significant portion of local air pollution at airports and are rarely modeled in conjunction with operational and meteorological variables. Although numerous studies focus on fuel burn or emission factors based on the ICAO LTO cycle, limited research integrates real-world airport conditions. In this article, CO<sub>2</sub>, NO<sub>x</sub>, CO, and HC emissions during the taxi-out phase at Istanbul Airport for the period 2024–2030 were estimated by considering the technical specifications of aircraft, operational delays, and meteorological visibility indices. Detailed analyses were conducted under three categories (Best, Normal, Worst) and 12 scenarios, and the daily intensity of emissions per unit area was evaluated according to the IDLH health risk indicator. In the estimation study, a new hybrid method called the FoREC-HHO algorithm was developed and compared with machine learning, metaheuristic algorithms, and statistical techniques. As a result of the analysis, the FoREC-HHO algorithm showed the highest accuracy rate for all emission types and achieved the lowest MAE values, demonstrating superior prediction performance. According to the analysis findings, in the worst-case scenario, CO<sub>2</sub> emissions increased by 80 %, NO<sub>x</sub> by 76 %, HC by 78 %, and CO by 66 % between 2024 and 2030. In the normal scenario, the emission increases were observed as 57 % for CO<sub>2</sub>, 52 % for NO<sub>x</sub>, 53 % for HC, and 46 % for CO. In contrast, under the best-case scenario, these increases were considerably more moderate, measured at 34 % for CO<sub>2</sub>, 31 % for NO<sub>x</sub>, 30 % for HC, and 26 % for CO. In addition, by 2030, the risk density for CO<sub>2</sub> is projected to reach 2.33 kg/m<sup>2</sup>/day, while for CO, this value is 0.01293 kg/m<sup>2</sup>/day. The calculated densities for NO<sub>x</sub> and HC were determined to be 0.00221 and 0.00030 kg/m<sup>2</sup>/day, respectively. These values were found to potentially pose high acute toxicity risks for CO, chronic respiratory and nervous system risks for NO<sub>x</sub> and HC, and climate-related effects and physiological burdens on personnel working in enclosed spaces for CO<sub>2</sub>. In this study, a comprehensive approach was presented for both temporal and seasonal estimation of emissions associated with the taxi-out process at airports and health-based risk assessment using the newly developed FoREC-HHO algorithm.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102954"},"PeriodicalIF":3.6,"publicationDate":"2025-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145733853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-05DOI: 10.1016/j.jairtraman.2025.102949
Fabian Kianpour
{"title":"Service innovations in airlines: A frontline employee perspective","authors":"Fabian Kianpour","doi":"10.1016/j.jairtraman.2025.102949","DOIUrl":"10.1016/j.jairtraman.2025.102949","url":null,"abstract":"","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102949"},"PeriodicalIF":3.6,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-05DOI: 10.1016/j.jairtraman.2025.102927
Xiaoyao Zhao, Xuting Sun
In aviation operations, the airline and maintenance service provider (MSP) have a close collaborative relationship, and their operational decisions often influence each other. However, in practical operational environments, flight delays negatively affect both stakeholders involved in this decision-making system, which reduces the robustness of the tactical decisions and overall system performance at the operational level. To address this issue, we propose a novel bilevel optimization framework that explicitly models the interaction between maintenance resource allocation and aircraft routing with the consideration of primary delay and delay propagation. To tackle the intrinsic complexity of this NP-hard problem, we design an accelerated bilevel solution approach that integrates customized heuristics for practical scalability. By enabling iterative coordination between the MSP and the airline, our approach allows both parties to optimize their tactical decisions in response to operational disruptions, thereby systematically enhancing the robustness of both aircraft maintenance and routing decisions. Extensive experiments on real-world datasets validate the effectiveness and robustness of the proposed framework. Based on seven weekly scenarios, the results show that the proposed bilevel model achieves reduction on the number of flight cancellations and yields notable day-of-operation savings. Comparative results verify that this collaborative decision-making mechanism yields lower operational costs for the airline and improved service efficiency for the MSP, consistently outperforming several baseline models which neglect delay propagation or collaborative mechanisms. These findings demonstrate the potential of our framework as well as solution approach as an intelligent decision support tool for addressing delay-induced disruptions in aircraft maintenance routing. Some actionable insights suach as proactive and flexiable maintenance operations via re-routing are obtained as well.
{"title":"Data-driven collaborative optimization between the airline and maintenance service provider: A Bi-level acceleration framework","authors":"Xiaoyao Zhao, Xuting Sun","doi":"10.1016/j.jairtraman.2025.102927","DOIUrl":"10.1016/j.jairtraman.2025.102927","url":null,"abstract":"<div><div>In aviation operations, the airline and maintenance service provider (MSP) have a close collaborative relationship, and their operational decisions often influence each other. However, in practical operational environments, flight delays negatively affect both stakeholders involved in this decision-making system, which reduces the robustness of the tactical decisions and overall system performance at the operational level. To address this issue, we propose a novel bilevel optimization framework that explicitly models the interaction between maintenance resource allocation and aircraft routing with the consideration of primary delay and delay propagation. To tackle the intrinsic complexity of this NP-hard problem, we design an accelerated bilevel solution approach that integrates customized heuristics for practical scalability. By enabling iterative coordination between the MSP and the airline, our approach allows both parties to optimize their tactical decisions in response to operational disruptions, thereby systematically enhancing the robustness of both aircraft maintenance and routing decisions. Extensive experiments on real-world datasets validate the effectiveness and robustness of the proposed framework. Based on seven weekly scenarios, the results show that the proposed bilevel model achieves reduction on the number of flight cancellations and yields notable day-of-operation savings. Comparative results verify that this collaborative decision-making mechanism yields lower operational costs for the airline and improved service efficiency for the MSP, consistently outperforming several baseline models which neglect delay propagation or collaborative mechanisms. These findings demonstrate the potential of our framework as well as solution approach as an intelligent decision support tool for addressing delay-induced disruptions in aircraft maintenance routing. Some actionable insights suach as proactive and flexiable maintenance operations via re-routing are obtained as well.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102927"},"PeriodicalIF":3.6,"publicationDate":"2025-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682225","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-04DOI: 10.1016/j.jairtraman.2025.102953
Tianyu Zhao, Jose Escribano, Arnab Majumdar, Washington Yotto Ochieng
This paper presents a robust algorithm for three-dimensional dynamic airspace sectorization, introducing for the first time multilayer traffic networks in the study field. Distinct from widely used meta-heuristic algorithms, this approach delivers consistent results for the same traffic scenario, avoiding the instability of stochastic search techniques. This approach uses a graph-based model, taking the air traffic network as input, based on which we calculate traffic complexity. To quantify the complexity assigned to the network, we employ two parameters: one derives from the traffic scenarios based on flight vectors, and the other from the network topology. Using this complexity-weighted network as input, a multi-layer spectral clustering algorithm is applied to generate the desired number of communities. To achieve an ideal sector structure, we introduce a boundary refinement framework to produce smooth and tightly connected three-dimensional sectors. The performance of the proposed algorithm is validated using three Key Performance Indicators (KPIs): workload, sector flight time, and dynamic density, demonstrating its capability to generate more load-balanced sector configurations compared to both the current UK operational sectors and the widely used Voronoi diagram-based methods. The performance of the algorithm is evaluated through eight experiments under both peak and off-peak traffic conditions, including four-hour short-term and four six-hour long-term scenarios, with the number of target sectors kept consistent with the operational configuration. The reduced standard deviations and coefficients of variation of the KPIs indicate that the proposed sectorization achieves a more balanced distribution of traffic loads across sectors. This research provides Air Navigation Service Providers (ANSPs) with an automatic tool for three-dimensional airspace sectorization, enabling more balanced workload distribution while adapting to evolving air traffic flow patterns.
{"title":"Robust 3D dynamic airspace sectorization: A multilayer graph-based approach","authors":"Tianyu Zhao, Jose Escribano, Arnab Majumdar, Washington Yotto Ochieng","doi":"10.1016/j.jairtraman.2025.102953","DOIUrl":"10.1016/j.jairtraman.2025.102953","url":null,"abstract":"<div><div>This paper presents a robust algorithm for three-dimensional dynamic airspace sectorization, introducing for the first time multilayer traffic networks in the study field. Distinct from widely used meta-heuristic algorithms, this approach delivers consistent results for the same traffic scenario, avoiding the instability of stochastic search techniques. This approach uses a graph-based model, taking the air traffic network as input, based on which we calculate traffic complexity. To quantify the complexity assigned to the network, we employ two parameters: one derives from the traffic scenarios based on flight vectors, and the other from the network topology. Using this complexity-weighted network as input, a multi-layer spectral clustering algorithm is applied to generate the desired number of communities. To achieve an ideal sector structure, we introduce a boundary refinement framework to produce smooth and tightly connected three-dimensional sectors. The performance of the proposed algorithm is validated using three Key Performance Indicators (KPIs): workload, sector flight time, and dynamic density, demonstrating its capability to generate more load-balanced sector configurations compared to both the current UK operational sectors and the widely used Voronoi diagram-based methods. The performance of the algorithm is evaluated through eight experiments under both peak and off-peak traffic conditions, including four-hour short-term and four six-hour long-term scenarios, with the number of target sectors kept consistent with the operational configuration. The reduced standard deviations and coefficients of variation of the KPIs indicate that the proposed sectorization achieves a more balanced distribution of traffic loads across sectors. This research provides Air Navigation Service Providers (ANSPs) with an automatic tool for three-dimensional airspace sectorization, enabling more balanced workload distribution while adapting to evolving air traffic flow patterns.</div></div>","PeriodicalId":14925,"journal":{"name":"Journal of Air Transport Management","volume":"132 ","pages":"Article 102953"},"PeriodicalIF":3.6,"publicationDate":"2025-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145682223","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-03DOI: 10.1016/j.jairtraman.2025.102936
Georg Hirte , Johannes Jaekel , Hans-Martin Niemeier
The paper examines the horizontal efficiency of aircraft approaches in the lower airspace. We propose two measures for horizontal efficiency and study the determinants, notably air traffic control's choice variables, of both efficiency metrics using robust (MM) and Tobit regression analyses. Our metrics indicate an average deviation from the optimum efficiency of 21.6 % and 19.6 %, respectively. We calculate that these inefficiencies generate approximately 165,088 tons of CO2 emissions and fuel costs of around € 23.8 million per annum. Improving the efficiency of approaches is thus a means to reduce aviation's externalities and lower its negative impact on the climate and noise. The metrics are significantly affected by the volume of flights, aircraft weight, weather threats, and the decision variables of air traffic control, which are runway change, runway choice and route choice. This is evidence that air traffic control can contribute to horizontal efficiency and reduce externalities.
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