Flight Schedule Research Articles

A Data-Driven Heuristic Method for Irregular Flight Recovery

In this study, we develop a data-driven heuristic method to solve the irregular flight recovery problem. Based on operational data from China South Airlines, Beijing, China, we evaluate the importance of a flight in the flight network and the influence of a delay on a flight and its subsequent flights. Then, we classify historical states into three scenarios according to their delay reasons and investigate the recovery patterns for each scenario. Inspired by the results of the data analysis, we develop a heuristic algorithm that imitates dispatcher actions. The algorithm is based on two basic operations: swapping the tail numbers of two flights and resetting their flight departure times. The algorithm can provide multiple recovery plans in real time for different scenarios, and we continue to refine and validate the algorithm for more robust and general solutions through a cost analysis. Finally, we test the efficiency and effectiveness of the recovery method based on the flight schedule, with real and simulated delays, and compare it with two other methods and the recovery actions of dispatchers.

Analisis Informasi Status Keberangkatan Penerbangan Oleh Unit Customer Service PT. Angkasa Pura II Bandar Udara Internasional Husein Sastranegara Bandung

Process of providing information unit Customer Service Husein Sastranegara International Airport experienced a discrepancy in flight status information between FIDS and AAS at the departure untill passengers were confused because they received different information from each of the information facilities. Purpose this study is determine process of services provided, constraints, and efforts in the process of information services provided. This research was conducted using a qualitative analysis, which tried to describe all conditions that existed, condition of symptoms according to what they were at the time research was conducted. Based on the main problem, namely to analyze the constraints and what efforts are made by information unit Customer Service when there is a difference in scheduled departure flight information. Result of the study show that the flow of service information on status of departure exists in the unit Customer Service Husein Sastranegara International Airport refers to Standard Operating Procedure of PT. Angkasa Pura II 2022 with the aim of providing fast, precise and accurate information services. Constraints on differences in information caused by miscommunication with other unit and less information service staff. Listening detail every Announcement, contacting related units, teamwork and additional personnel are efforts to overcome the obstacles encountered.

Modelling and simulation of urban air mobility: an extendable approach

This paper presents an extendable approach to the modelling and simulation of Urban Air Mobility (UAM), and dissemination criteria for system of systems simulation driven studies. UAM involves a multitude of complexities including the airspace, fleet, demand, and vertidrome management. Simulation is a key enabler for understanding these complexities and the interaction of the different stakeholders within the UAM paradigm. This work builds upon past research of the authors and presents a framework for simulation and modelling which includes the modelling of passenger demand, passenger mode choice, vehicle allocation for heterogenous fleets, route planning, deadheading, vertidrome scheduling, and flight scheduling with stop-overs. The approach presented in this work can be used to model both on-demand and scheduled operations, while the primary focus is placed on the former. Moreover, different methods can be implemented for the detailed modelling of the stakeholders, in addition to parametrically varying aspects such as the fleet size, number of vertidromes, and others. The aims of this paper are two, firstly to offer a framework for the modelling of UAM by breaking down its complexity systematically to simpler blocks, namely the stakeholders, the processes and interaction, through which the emergent behavior of the system of systems simulation may be more easily observed or understood. Secondly, it is to provide a clear method for dissemination of the modelling and simulation with the goal of establishing a common standard, demonstrated through the dissemination of the authors’ simulation to the reader.

Airlines Strategy Adjustment during COVID-19

This an article to study on the strategic adjustment of the airline business during the crisis of COVID-19 as suggestions and guidance for adjusting the strategies of the organization during the crisis. Along with work management and internal management, as the current COVID-19 epidemic continues and there is no cure for COVID-19. The impact of the crisis is severely affecting to Airline business including the suspension of unnecessary flights path restrictions. Until the cessation of the flight according to the measures of the World Health Organization and prevent the outbreak. Therefore, airlines have been adapted to keep up with the most efficiency. So that the organization can survive. According to the study, it was found that strategies of the airline business. It helps the airlines to continue their business in this crisis. Under certain conditions and limitations established, and not contrary to the Air Navigation Act including reducing the number of working days, new flight schedule management with passenger numbers, Flight cancellation, setting the minimum number of passengers before flight assignments, Wage reduction and the end is to reduce the number of employees. The organization will choose as last as reduce staff. To cut the unemployment rate and affect the economy of the country. Therefore, the aviation industry is an important factor driving the global economy.

Air Traffic Management Using a GPU-Accelerated Genetic Algorithm

Abstract Air traffic management is becoming highly complex with the rapid increase in the number of commercial and cargo flights, leading to increased traffic congestion and flight delays. To mitigate these issues, we present a flight path generation system that distributes the aeroplanes across the airspace and imparts minimal delays to the flight if required, thus ensuring that the aircraft follows the shortest route wherein it encounters the least amount of traffic. We develop a parallel genetic algorithm in CUDA-C with a novel fitness function allowing the system to reach an optimal solution where the air traffic density is minimised. The proposed algorithm was tested on one day's domestic flight schedule and achieved an 18% reduction in traffic density, with the flight times and delays remaining proportional to the data observed in the existing air traffic management system.

Analysis of the Use of Aviobridge to Improve on Time Performance at Jenderal Ahmad Yani International Airport Semarang

The time factor is a crucial factor in airlines. So that the timeliness of on time performance (OTP) is important in the world of aviation. This study aims to determine the use of aviobridge and the impact of using aviobridge in increasing on time performance at Jenderal Ahmad Yani International Airport Semarang. This research uses a quantitative descriptive method. The population and sample of this study are monthly airline data including flight schedule data, actual airline data, on time airline data, and airline data using aviobridge. The data analysis carried out consisted of reduction, data presentation, and drawing conclusions. The results of this study indicate that there is an influence from the use of aviobridge on on time performance at General Ahmad Yani International Airport Semarang with H1 accepted because there are significant results from the two variables. These results show that in December 2022 the total average use of aviobridge was 155.7%, which affected delays with an average of 22% and a ratio of 1:1.13.

A two-stage approach to aircraft recovery under uncertainty

The paper presents a two-stage approach for minimizing the impact of daily disruptions on an airline’s published flight schedule. The problem is characterized by uncertainty in the duration of the disruption and the point in time when its length becomes known. Both a single-commodity network model and multi-commodity network model with side constraints are developed to first determine the flights that are most likely to be affected, and then to adjust their schedules to achieve system-wide optimality. The overall objective is to minimize the weighted sum of total passenger delay costs, cancellation costs, curfew violation costs, and variation from the original schedule. The two types of uncertainty are addressed by examining a range of scenarios that reflect the most likely outcomes. The results provide guidance and a measure of robustness for the flight director as the disruption unfolds. A rolling horizon approach that closely mimics current procedures used by several airlines is also presented to provide a benchmark for comparisons with the two-stage solutions.

Engineering and navigating calculation the flight of unmanned aircrafts of tactical class

The regulatory documents of the Ministry of Defense of Ukraine provide for navigational training of the crews of unmanned aircraft complexes and establish the necessity of having a navigational plan and an engineering-navigator flight calculation at the workplace of an external UAV pilot. The article notes that today there are no normative documents that would establish the content and scope of engineering and navigational calculations and methods of their implementation for unmanned aircraft complexes of tactical classes. The article as a whole is devoted to the consideration of issues of methodical support of navigator training of crews of unmanned aerial systems of the tactical class with an electric power plant. It is indicated that, based on the tactical and technical capabilities of UAVs of tactical classes, the nature of the tasks performed by them and the typical educational level of their external pilots, the creation of the most simplified methodology for performing basic engineering and navigational calculations of UAV flights is required. The mathematical complexity of such a method should not go beyond general secondary education. When performing navigational calculations of aircraft flights, the main difficulty is created by the problem of taking into account the influence of the wind. Simple algorithms for calculating the correction to the wind drift course, road speed and flight duration on straight sections of the route and sections of U-turns in the presence of wind are proposed. Algorithms for calculating the total need for energy resources for a flight along a given route and for separate sections of the route, including additional energy resource needs for sections of altitude gain, are proposed. Recommendations for evaluating the energy capacity of the battery available for flight performance are given. An algorithm for calculating the critical reserve of energy resources, which is necessary for the possibility of returning the UAV from the farthest point of the route under meteorological conditions for the scheduled flight time, is proposed. Options for full and abbreviated engineering and navigational calculations are offered.

Prediction of departure flight delays through the use of predictive tools based on machine learning/deep learning algorithms

Abstract The objective of this research is to predict the delays in the departure of scheduled commercial flights through a methodology that uses predictive tools based on machine learning/deep learning (ML/DL), with supervised training in regression, based on the available flight datasets. Since the novel contribution of this work is, first, to make the comparison of the predictions in terms of means and statistical variance of the different ML/DL models implemented and, second, to determine the coefficients of the importance of the features or flight attributes, using ML methods known as permutation importance, it is possible to rank the importance of flight attributes by their influence in determining the delay time and reduce the problem of selecting the most important flight attributes. From the results obtained, it is worth mentioning that the model that presents the best performance is the ensemble or combinatorial method of random forest regressor models, with an acceptable prediction range (measured with the root-mean-square-error).

A stochastic optimization approach for optimal Tail Assignment with knowledge-based predictive maintenance

AbstractRecent developments in the field of data analysis offer enormous potential to derive predictions of future aircraft maintenance necessities from observable aircraft attributes. This procedure is called Predictive Maintenance. The Predictive Maintenance generates considerable business benefits compared to alternatives like reactive or preventive maintenance for various reasons. Nevertheless, recognizing a maintenance necessity is only the first step, since the execution of the maintenance action has to fit into the airlines operational schedule. An essential step to realize financial benefits is to integrate Predictive Maintenance into the airlines optimization processes. To contribute to this task, we expand a well-known Tail Assignment model for the assignment of a potentially heterogeneous fleet of aircraft to a schedule of flights by a number of part failure scenarios. This results in a stochastic mixed integer linear optimization program, for which an optimization algorithm with solution guarantees is developed. This optimization algorithm is based on Benders Decomposition, which is concretized for the Tail Assignment problem and optimized for this task. Using this algorithm, a large proportion of the recovery costs for almost all instances tested is saved. The algorithm solves all instances in a reasonable amount of time. The algorithm uses a state-of-the-art mixed-integer linear solver, implementing a decomposition-based solution procedure for stochastic programs, called the L-shaped method. To demonstrate the potential of the approach, we benchmark our results using four strategies, motivated by commonly used preventive, reactive and passive approaches. Our approach leads to considerable cost savings when compared to each of the four benchmark approaches. The algorithms are tested on a set of instances with up to 80 flights based on a pre-pandemic schedule of a larger German airline. To the best of our knowledge, this article presents the first attempt to implement an exact optimization approach integrating malfunction predictions of the form presented into a Tail Assignment model.

Analyzing factors affecting charter flight service demand: A case of Taiwan

Global charter flight demand remined relatively stable over the last decades, and international charter flight is an integrated product of the aviation and tourism industries. To better understand charter flight tourism in Asia, this study analyses key reasons affected Taiwan’s charter flight demand from Japan, South Korea, Malaysia, and Singapore during the period 2009‒2018, with a consideration of aviation- and tourism-related variables. Empirical results show that the reduction in scheduled flight aircraft size stimulated new charter flight demand to Taiwan, offsetting the negative effects caused by scheduled seat increment to a certain degree. This study contributes to literature by exploring the impact of scheduled flight service availability on charter flight demand, and further enriches our understanding of the impact of scheduled flight services on international tourist arrivals in terms of aircraft size. Importantly, it has implications for policymakers and stakeholders involved in charter business, assisting them in facilitating aviation and tourism recovery during the post-COVID-19 era.

Hedonic preference of airline passengers

The purpose of this study is to determine which airlines Davao City-bound and outbound passengers prefer. Passenger information was acquired via survey questionnaires employing the Likert scale. In this study, non-experimental quantitative research employing a casual research method was employed. Using descriptive and informal research methodologies, this study investigated whether demographic variables and airline service quality influence the airline service choices of Davao City passengers. This investigation employs artificial neural network research to determine which factors influence airline preference. The majority of air carrier respondents are between the ages of 21 and 35, are predominantly female, and are employed by private companies. The airline preferences of passengers are influenced by price, cabin services, flight schedule, safety, on-time performance, and employee conduct. Important airline demographics included age, occupation, and sex. Price is the most significant criterion when selecting an airline, followed by flight schedule, on-time performance, and employee conduct. Flights should offer discounts to students and senior citizens. They may adjust fares based on the findings. To attract a broader age range of customers, airlines should strategically organize their marketing and focus on specific market niches. To increase sales, airlines may consider offering discounted, low-cost, or one-peso fares during certain times. To assist time-sensitive travelers in reaching their destinations in the event of airline delays or cancellations, alternative flights are advised. To gain a deeper understanding of airline carrier selection, research should be extended, employing a larger sample or alternative statistical methods.

Flight Reservation System

Flight Reservation System

Network science approach for identifying disruptive elements of an airline

Currently, flight delays are common and they propagate from an originating flight to connecting flights, leading to large disruptions in the overall schedule. These disruptions cause massive economic losses, affect airlines’ reputations, waste passengers’ time and money, and directly impact the environment. This study adopts a network science approach for solving the delay propagation problem by modeling and analyzing the flight schedules and historical operational data of an airline. We aim to determine the most disruptive airports, flights, flight-connections, and connection types in an airline network. Disruptive elements are influential or critical entities in an airline network. They are the elements that can either cause (airline schedules) or have caused (historical data) the largest disturbances in the network. An airline can improve its operations by avoiding delays caused by the most disruptive elements. The proposed network science approach for disruptive element analysis was validated using a case study of an operating airline. The analysis indicates that potential disruptive elements in a schedule of an airline are also actual disruptive elements in the historical data and they should be considered to improve operations. The airline network exhibits small-world effects and delays can propagate to any part of the network with a minimum of four delayed flights. Finally, we observed that passenger connections between flights are the most disruptive connection type. Therefore, the proposed methodology provides a tool for airlines to build robust flight schedules that reduce delays and propagation.

Research on Flight Schedule Optimization Based on Different Runway Operation Modes

The update and iteration of the airport facilities completed in the runway operation system raise a request for more scientific control operation restrictions. In the old, optimized method of flight slot, no consideration was given to the runway operation strategy. As a result, the flight slot failed to meet the operation restriction and would incur unavoidable delays. This paper sets the research objective as the system composed of an apron, runway entrance and exit, and parallel runway. It focuses on matching the corresponding relationship between time and space of flights in the studied system. It establishes three flight slot optimization models to meet the requirements of isolated operation, semi-mixed operation, and mixed operation, respectively. On a practical level, the computer simulation software AirTOp is employed for simulation verification in the example of Wuhan Tianhe Airport. The results show that the delay in the isolation operation mode is reduced by about 59%, the semi-mixed operating mode reduces delays by about 48%, and mixed operating mode delays are reduced by approximately 52%. Therefore, it proves its feasibility of effective reduction in overall delay and its ability to provide decision support for the allocation of the flight time resource in parallel dual runway airports.

A Time-and-Space-Network-Based Green Fleet Planning Model and Its Application for a Hub-and-Spoke Network

Most previous studies on airline fleet planning have focused solely on economic considerations, neglecting the impact of carbon reduction. This paper presents a novel method for green fleet planning, using a bi-level programming model to balance conflicts among stakeholders while considering uncertain parameters such as demand and operating costs. The upper model aims to reduce carbon emissions by taking into account government constraints, such as carbon allowances and carbon prices, as well as airline satisfaction. The lower model seeks to maximize airline revenue using a space-and-time network model based on given airline flight schedules. To verify the game model, a case study utilizing randomly generated scenarios is employed within the context of China’s aviation-specific emissions trading scheme. Results show that: (1) compared to the scenario without a policy aiming at reducing carbon emissions, this method reduces carbon emissions by 23.03% at the expense of a 6.96% reduction in terms of the airline’s operating profit; (2) when passenger demand levels increase to 160%, the profitability of the proposed fleet increases by 50.83%, while there were only insignificant changes in carbon emissions; (3) the proposed methodology can assist the airlines systematically to reduce carbon emissions and provide valuable strategic guidance for policy makers.

A Novel Flight Dynamics Modeling Using Robust Support Vector Regression against Adversarial Attacks

<div>An accurate Unmanned Aerial System (UAS) Flight Dynamics Model (FDM) allows us to design its efficient controller in early development phases and to increase safety while reducing costs. Flight tests are normally conducted for a pre-established number of flight conditions, and then mathematical methods are used to obtain the FDM for the entire flight envelope. For our UAS-S4 Ehecatl, 216 local FDMs corresponding to different flight conditions were utilized to create its Local Linear Scheduled Flight Dynamics Model (LLS-FDM). The initial flight envelope data containing 216 local FDMs was further augmented using interpolation and extrapolation methodologies, thus increasing the number of trimmed local FDMs of up to 3,642. Relying on this augmented dataset, the Support Vector Machine (SVM) methodology was used as a benchmarking regression algorithm due to its excellent performance when training samples could not be separated linearly. The trained Support Vector Regression (SVR) predicted the FDM for the entire flight envelope. Although the SVR-FDM showed excellent performance, it remained vulnerable to adversarial attacks. Hence, we modified it using an adversarial retraining defense algorithm by transforming it into a Robust SVR-FDM. For validation studies, the quality of predicted UAS-S4 FDM was evaluated based on the Root Locus diagram. The closeness of predicted eigenvalues to the original eigenvalues confirmed the high accuracy of the UAS-S4 SVR-FDM. The SVR prediction accuracy was evaluated at 216 flight conditions, for different numbers of neighbors, and a variety of kernel functions were also considered. In addition, the regression performance was analyzed based on the step response of state variables in the closed-loop control architecture. The SVR-FDM provided the shortest rise time and settling time, but it failed when adversarial attacks were imposed on the SVR. The Robust-SVR-FDM step response properties showed that it could provide more accurate results than the LLS-FDM approach while protecting the controller from adversarial attacks.</div>

Operational Analysis of the Apron Movement Control (AMC) Unit in Handling Aircraft at Abdulrachman Saleh Airport Apron Malang

Apron Movement Control (AMC) is an airport personnel who has a license and rating to carry out duties as responsible for flight operations, supervision, aircraft movement, vehicle traffic, passengers and cleanliness supervision in the airside area and records flight data on the apron. Supervision carried out by AMC aims to create flight security and safety and create discipline from service users which can affect activities on the air side. The purpose of this study was to find out how the Apron Movement Control (AMC) Unit Standard Operational Procedure is in handling aircraft on the apron and the obstacles faced by the AMC unit at Abdulrachman Saleh Airport Malang. This research is a qualitative research using primary data and secondary data. Data collection techniques used are observation, interviews and documentation. The observation is to conduct a review or direct observation in the working area of the AMC unit. The interviews in this study were AMC officers consisting of the head of the AMC unit and 2 personnel. The documentation is collecting data at the time of observation and interviews, as well as taking pictures during field activities. The results of this study can be concluded that the Standard Operational Procedure unit Apron Movement Control (AMC) in handling aircraft on the apron, namely service and supervision. Services, namely arranging aircraft movements, plotting parking stands, services for emergency aircraft using follow me vehicles. Then the supervision referred to is supervision of vehicle traffic, movement of people/passengers, loading and unloading of goods, routine inspections of FOD, supervision during refueling, and when the engine is running up. The performance of AMC officers is said to be good because they carry out their duties in accordance with the Standard Operating Procedure (SOP) from the Ministry of Transportation and UPT. Obstacles in operational activities, namely the determination of parking stands still refers to the Indonesian Air Force and radio communications that often break up between ATC and AMC, AMR's accurate data is delayed in entering ATC and GH/airline units, heavy damage to aprons and taxiways, and airlines are late in delivering flights schedule. The solution to this problem is that the AMC unit holds internal and external meetings with ATC, GH and the Indonesian Air Force, so that the three parties can determine the best solution regarding flight operations.

On the Transition to Green Aviation

To solve the problem of harmful emissions into the atmosphere, the principles of “green aviation” have been developed, which are based on optimizing flight schedules, changing the aircraft design, using lightweight composite materials, changing the engine operation principle and design, and the fuel used. The staff of the National Research Center Zhukovsky Institute, working jointly with other institutes, develops the principles of “green aviation”. Over the past few years, specialists of the Zhukovsky Institute have developed a number of powerful switching voltage converters as part of power plants for electric and hybrid aircrafts, in particular, for charging aircraft on-board storage batteries. Owing to the use of modern solid-state electronic components and an ergonomic design, the power plant specific capacity has been brought to a level from units to tens of kW/kg. In the field of low-temperature plasma physics, work is also underway on electrohydrodynamic flow control systems for aircraft, which is of primary importance for increasing aerodynamic and energy efficiency, thus helping solve the environmental problem of reducing harmful emissions, including carbon and nitrogen oxides, and achieve significant fuel saving.

An Empirical Analysis of the Aircraft Emissions by Operating from Scheduled Flights within the Domestic Market in Spain

Over the past 20 years, civil aviation has substantially reduced its environmental impact to augment sustainable transportation. In Spain, the domestic market has been habitually characterized by a few enterprises providing air transport services linked to scheduled flights on domestic corridors. Because of geographic diversity and the highly concentrated population characterizing this southern European country, many of them could not be supplied by alternative transport modes in terms of both time and distance by comparison with air transportation. For air quality monitoring from 139 national corridors, this paper aims to study related aviation emissions to conduct an economic analysis in terms of positive or negative externalities. For such purposes, the study focused on these domestic routes served by the five most important Spanish airports, specifically on the number of passengers transported from 2011 to 2020. Up to 10 aircraft types representing no more than 89% of regular operations on these flyways were subsequently identified. In addition, certain engine types also were selected as representatives to evaluate their emissions, depending on the great-circle distance in each route. The research findings, though particularly conditioned by aviation peculiarities of such a domestic market, point decisively to significant dependence upon emissions in connection with the seasonality of the demand and the concentration of flights with low occupancy indices from any one of them. Results suggest that airlines would benefit from operating turboprops instead of turbojets on selected routes, especially when oil prices are high. However, it is not always easy to find a balance between uncompromising economic profitability and effective fleet availability, since nowadays air transport undertakings tend to unify their fleets by using a few aircraft families, mostly powered by jet engines, apart from regional carriers.