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The purpose of this paper is to design a new standard instrument arrival called the point merge system (PMS) for converging runways. The PMS enables controllers to handle traffic with no heading instruction, as well as aiming to reduce a controller's frequency occupancy time.

The point merge model was designed for converging runways. Istanbul International Ataturk Airport, which has converging runways, was chosen as an application area for this model. The same 50 traffic arrivals per hour were used both for point merge and vectoring. Implementation was compared using a real time simulation.

The simulation results show that the total average number of instructions is about 33 per cent less and the frequency occupancy is about 37 per cent less for point merge than for vectoring. In addition, in terms of trajectory dispersion, in point merge, traffic is within a narrower triangular area, while in vectoring large traffic dispersion occurs.

The point merge model for converging runways proposed in this paper can be applied by airspace designers and air navigation service providers to perform efficient standard instrument arrival routes.

The PMS has been developed for single and parallel runways; however, in this study, the point merge model is designed for converging runways at Istanbul International Ataturk Airport.

Metroplex is a system of two or more airports, in physical proximity, with highly interdependent arrival and departure operations. The purpose of this study is the construction of an efficient and effective air route model based on the point merge system (PMS) to reduce aircraft fuel consumption and CO₂ emissions for three metroplex airports in Istanbul terminal control area (TMA).

A PMS arrival route model is constructed for metroplex airports. In the proposed model, two situations are taken into consideration: for delay which can be defined as flying on sequencing legs (PMS_del) and for no delay (PMS_{no del}). An empirical model is developed using a data set including the flight data records of ten actual B737-800 domestic flights. With this empirical model, both the baseline and the PMS models (PMS_del and PMS_{no del}) are compared in terms of fuel consumption, CO₂ emissions and flight distance and time as a theoretical computation.

In the proposed PMS_{no del} arrival route model, according to different entry points for Istanbul Ataturk International Airport (LTBA), the analyses show an average reduction of 26 per cent in flight time, 24.5 per cent in flight distance, 17 per cent in fuel burned and CO₂ emissions; in addition, for Sabiha Gökcen International Airport (LTFJ) there are 34, 23 and 32 per cent average savings for flight time, flight distance and fuel burned together with CO₂ emissions obtained, respectively. Even if the PMS_del model, for LTFJ except only one entry point, for LTBA except two entry points, better results are obtained than baseline.

The point merge model for metroplex airports in this paper can be applied by airspace designers and Air Navigation Service Providers to perform efficient and effective arrival routes.

In this study, a point merge model is constructed for metroplex airports. Quantitative results, using an empirical model, are achieved in terms of fuel consumption, CO₂ emissions and flight distance and time at metroplex airports.

The purpose of this study is to provide conflict-free operations in terminal manoeuvre areas (TMA) using the point merge system (PMS), airspeed reduction (ASR) and ground holding (GH) techniques. The objective is to minimize both total aircraft delay (TD) and the total number of the conflict resolution manoeuvres (CRM).

The mixed integer linear programming (MILP) is used for both single and multi-objective optimization approaches to solve aircraft sequencing and scheduling problem (ASSP). Compromise criterion and ε-constraint methods were included in the methodology. The results of the single objective optimization approach results were compared with baseline results, which were obtained using the first come first serve approach, in terms of the total number of the CRM, TD, the number of aircraft using PMS manoeuvres, ASR manoeuvres, GH manoeuvres, departure time updates and on-time performance.

The proposed single-objective optimization approach reduced both the CRM and TD considerably. For the traffic flow rates of 15, 20 and 25 aircraft, the improvement of CRM was 53.08%, 41.12% and 32.6%, the enhancement of TD was 54.2%, 48.8% and 31.06% and the average number of Pareto-optimal solutions were 1.26, 2.22 and 3.87, respectively. The multi-objective optimization approach also exposed the relationship between the TD and the total number of CRM.

The proposed mathematical model can be implemented considering the objectives of air traffic controllers and airlines operators. Also, the mathematical model is able to create conflict-free TMA operations and, therefore, it brings an opportunity for air traffic controllers to reduce frequency occupancy time.

The mathematical model presents the total number of CRM as an objective function in the ASSP using the MILP approach. The mathematical model integrates air traffic controllers’ and airline operators’ perspective together with new objective functions.

The purpose of this paper is to create a new fuel flow rate model using cuckoo search algorithm (CSA) for the descending stage of the flight.

Using the actual flight data record data of the B737-800 aircraft, a new fuel flow rate model has been developed for this aircraft type. The created model is to predict the fuel flow rate with high accuracy depending on the altitude and true airspeed. In addition, the CSA fuel flow rate model was used to calculate the fuel consumption for the point merge system, which is used for combining the initial approach to the final approach at Istanbul Airport, the largest airport of Turkey.

As a result of the analysis, the correlation coefficient value is found as 0.996858 for Flight 1, 0.998548 for Flight 2, 0.995363 and 0.997351 for Flight 3 and Flight 4, respectively. The values that are so close to 1 indicate that the model predicts the real fuel flow rate data with high accuracy.

This model is considered to be useful in air traffic management decision support systems, aircraft performance models, models used for trajectory prediction and strategies used by the aviation community to reduce fuel consumption and related emissions.

The importance of this study lies in the fact that to the best of the authors’ knowledge, it is the first fuel flow rate model developed using CSA for the descent stage in the existing literature; the data set used is real values.

This study aims to evaluate the performance of the most popular multi-objective programming scalarization methods in the literature for the aircraft sequencing and scheduling problem (ASSP). These methods are the weighted sum method, weighted goal programming, the ε-constraint method, the elastic constraint method, weighted Tchebycheff and augmented weighted Tchebycheff.

First, the ASSP for a single runway case was modeled using mixed-integer programming considering the safety and operational constraints and the objectives of the minimization of total delay and total flight time for a sample airport. The objectives were then combined by using the multi-objective programming scalarization methods and various expected times of arrival–departure samples were run for the mathematical models. Finally, the methods were evaluated in terms of the number of nondominated solutions, superior nondominated solution and the average solution time using the Measurement of Alternatives and Ranking according to Compromise Solution method, which is a popular multi-criteria decision-making method.

Augmented Weighted Tchebycheff was found to be the most effective approach to ASSP in terms of the evaluation criteria followed by Weighted Tchebycheff and then weighted sum method.

The methodology presented in this study could provide more efficient air traffic management in terminal maneuvering areas when multiple objectives need to be optimized.

Although there are studies including the comparison of several scalarization methods for other problems, the comparison of the methods for ASSP has not yet been handled in the literature. As there are several stakeholders in the air traffic system, ASSP includes several objectives, and as a result, this problem can benefit from analyses using this comparison.

The purpose of this study is to develop and test a new deep learning model to predict aircraft fuel consumption. For this purpose, real data obtained from different landings and take-offs were used. As a result, a new hybrid convolutional neural network (CNN)-bi-directional long short term memory (BiLSTM) model was developed as intended.

The data used are divided into training and testing according to the k-fold 5 value. In this study, 13 different parameters were used together as input parameters. Fuel consumption was used as the output parameter. Thus, the effect of many input parameters on fuel flow was modeled simultaneously using the deep learning method in this study. In addition, the developed hybrid model was compared with the existing deep learning models long short term memory (LSTM) and BiLSTM.

In this study, when tested with LSTM, one of the existing deep learning models, values of 0.9162, 6.476, and 5.76 were obtained for R², root mean square error (RMSE), and mean absolute percentage error (MAPE), respectively. For the BiLSTM model when tested, values of 0.9471, 5.847 and 4.62 were obtained for R², RMSE and MAPE, respectively. In the proposed hybrid model when tested, values of 0.9743, 2.539 and 1.62 were obtained for R², RMSE and MAPE, respectively. The results obtained according to the LSTM and BiLSTM models are much closer to the actual fuel consumption values. The error of the models used was verified against the actual fuel flow reports, and an average absolute percent error value of less than 2% was obtained.

In this study, a new hybrid CNN-BiLSTM model is proposed. The proposed model is trained and tested with real flight data for fuel consumption estimation. As a result of the test, it is seen that it gives much better results than the LSTM and BiLSTM methods found in the literature. For this reason, it can be used in many different engine types and applications in different fields, especially the turboprop engine used in the study. Because it can be applied to different engines than the engine type used in the study, it can be easily integrated into many simulation models.

The purpose of this paper is to provide a feature‐based characterization of version control systems (VCSs), providing an overview about the state‐of‐the‐art of versioning systems dedicated to modeling artifacts.

Based on a literature study of existing approaches, a description of the features of versioning systems is established. Special focus is set on three‐way merging which is an integral component of optimistic versioning. This characterization is employed on current model versioning systems, which allows the derivation of challenges in this research area.

The results of the evaluation show that several challenges need to be addressed in future developments of VCSs and merging tools in order to allow the parallel development of model artifacts.

Making model‐driven engineering (MDE) a success requires supporting the parallel development of model artifacts as is done nowadays for text‐based artifacts. Therefore, model versioning capabilities are a must for leveraging MDE in practice.

The paper gives a comprehensive overview of collaboration features of VCSs for software engineering artifacts in general, discusses the state‐of‐the‐art of systems for model artifacts, and finally, lists urgent challenges, which have to be considered in future model versioning system for realizing MDE in practice.

The study here examines how business actors adapt to changes in networks by analyzing their perceptions or their network pictures. The study is exploratory or iterative in the sense that revisions occur to the research question, method, theory, and context as an integral part of the research process.

Changes within networks receive less research attention, although considerable research exists on explaining business network structures in different research traditions. This study analyzes changes in networks in terms of the industrial network approach. This approach sees networks as connected relationships between actors, where interdependent companies interact based on their sensemaking of their relevant network environment. The study develops a concept of network change as well as an operationalization for comparing perceptions of change, where the study introduces a template model of dottograms to systematically analyze differences in perceptions. The study then applies the model to analyze findings from a case study of Norwegian/Japanese seafood distribution, and the chapter provides a rich description of a complex system facing considerable pressure to change. In-depth personal interviews and cognitive mapping techniques are the main research tools applied, in addition to tracer studies and personal observation.

The dottogram method represents a valuable contribution to case study research as it enables systematic within-case and across-case analyses. A further theoretical contribution of the study is the suggestion that network change is about actors seeking to change their network position to gain access to resources. Thereby, the study also implies a close relationship between the concepts network position and the network change that has not been discussed within the network approach in great detail.

Another major contribution of the study is the analysis of the role that network pictures play in actors' efforts to change their network position. The study develops seven propositions in an attempt to describe the role of network pictures in network change. So far, the relevant literature discusses network pictures mainly as a theoretical concept. Finally, the chapter concludes with important implications for management practice.

Libraries have faced many periods of grim economic realities. These periods of hardship have forced libraries to strive for more efficient organizational structures. Many of these improved organizational structures have been the result of mergers and/or consolidations. This phenomenological study describes the lived experiences of the merger design team of a large and complex library organization.

Results indicated the experience of the participants touched upon each of Bolman and Deal’s (2008) four frames: political, human resources, structural, and symbolic. The merger design team’s effectiveness on task is congruent with the model of team effectiveness proposed by Hackman (2002). Lastly, the role of underlying assumptions, espoused values and beliefs, and artifacts that makes up the organization’s culture falls within the parameters set forth by Schein (2004).

A broad product assortment is usually valued highly by customers. However, holding a great number of product variants in inventory increases the costs of a supplier. It is possible to reduce need for warehousing with direct deliveries from manufacturing units, but customer value is reduced when orders are received on several shipments. Merge‐in‐transit is a distribution method in which goods shipped from several supply locations are consolidated into one final customer delivery while they are in transit. This article examines the effects of merge‐in‐transit distribution on delivery costs. The analysis is performed with a maintenance, repair, and operations products distributor as the case company. The evidence in this article supports the claim of merge‐in‐transit being a cost efficient distribution alternative in business networks. Based on the results advocates that companies in multi‐company networks should study the possibility of using the merge‐in‐transit delivery model.