This book combines the research activities of the authors, both of whom are researchers at Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation), and presents their findings from the last 15 years. Their work uses air transport as its focal point, within the realm of mathematical optimization, looking at real life problems and theoretical models in tandem, and the challenges that accompany studying both approaches. The authors’ research is linked with the attempt to reduce air space congestion in Western Europe, USA and, increasingly, Asia. They do this through studying stochastic optimization (particularly artificial evolution), the sectorization of airspace, route distribution and takeoff slots, and by modeling airspace congestion. Finally, the authors discuss their short, medium and long term research goals. They hope that their work, although related to air transport, will be applied to other fields, such is the transferable nature of mathematical optimization. At the same time, they intend to use other areas of research, such as approximation and statistics to complement their continued inquiry in their own field. Contents 1. Introduction. Part 1. Optimization and Artificial Evolution 2. Optimization: State of the Art. 3. Genetic Algorithms and Improvements. 4. A new concept for Genetic Algorithms based on Order Statistics. Part 2. Applications to Air Traffic Control 5. Air Traffic Control. 6. Contributions to Airspace Sectorization. 7. Contribution to Traffic Assignment. 8. Airspace Congestion Metrics. 9. Conclusion and Future Perspectives. About the Authors Daniel Delahaye works for Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation) in France. Stéphane Puechmorel works for Ecole Nationale de l’Aviation Civile (French National School of Civil Aviation) in France.

Modelling and Managing Airport Performance provides an integrated view of state-of-the-art research on measuring and improving the performance of airport systems with consideration of both airside and landside operations. The considered facets of performance include capacity, delays, economic costs, noise, emissions and safety. Several of the contributions also examine policies for managing congestion and allocating sparse capacity, as well as for mitigating the externalities of noise, emissions, and safety/risk. Key features: Provides a global perspective with contributing authors from Europe, North and South America with backgrounds in academia, research institutions, government, and industry Contributes to the definition, interpretation, and shared understanding of airport performance measures and related concepts Considers a broad range of measures that quantify operational and environmental performance, as well as safety and risk Discusses concepts and strategies for dealing with the management of airport performance Presents state-of-the-art modelling capabilities and identifies future modelling needs Themed around 3 sections – Modelling Airport Performance, Assessing Airport Impacts, and Managing Airport Performance and Congestion Modelling and Managing Airport Performance is a valuable reference for researchers and practitioners in the global air transportation community.

This book reviews operations research theory, applications and practice in airline planning and operations. It examines the business and technical landscape, details best practices, and identifies open questions and areas for future research.

The book is dedicated as an auxiliary literature for academic staff of universities, research institutes, as well as for students of transport teaching. The aim of the conference was to present the achievements of national and foreign research and scientific centers dealing with the issues of rail, road, air and sea transport in technical and technological aspects, as well as organization and integration of the environment conducting research and education in the discipline of civil engineering and transport. International Scientific Conference Transport of the 21st Century was held in Ryn, Poland, in the 9th–12th of June 2019. The research areas of the conference were as follows: • transport infrastructure and communication engineering, • construction and operation of means of transport, • logistics engineering and transport technology, • organization and planning of transport, including public transport, • traffic control systems in transport, • transport telematics and intelligent transportation systems, • smart city and electromobility, • safety engineering and ecology in transport, • automation of means of transport. It also used by specialists from central and local government authorities in the area of deepening knowledge of modern technologies and solutions used for planning, managing and operating transport.

This volume presents new concepts and methods in Air Traffic Management, in particular: Collaborative Decision Making, as it incorporates for the first time airline companies in the management process; Congestion Pricing, as many part of the systems are and will remain saturated, hence only leveling of demand can contribute to global efficiency; Flow Management Methods, as the most important tools in planning and analysis; Models of Controller-Pilot Interaction, as deregulation increases the workload of this communication; Weather Forecast, as airport capacity is strongly affected by weather conditions.

260 2 Crew Legalities and Crew Pairing Repair 264 3 Model and Mathematical Formulation 266 4 Solution Methodology 271 5 Computational Experiences 277 6 Conclusion 285 REFERENCES 286 10 THE USE OF OPTIMIZATION TO PERFORM AIR TRAFFIC FLOW MANAGEMENT Kenneth Lindsay, E. Andrew Boyd, George Booth, and Charles Harvey 287 1 Introduction 288 2 The Traffic Flow Management (TFM) Problem 289 3 Recent TFM Optimization Models 292 4 The Time Assignment Model (TAM) 302 5 Summary and Conclusions 307 REFERENCES 309 11 THE PROCESSES OF AIRLINE SYSTEM OPERATIONS CONTROL Seth C. Grandeau, Michael D. Clarke, and Dennis F.X. Mathaisel 312 1 Introduction 313 2 The Four Phases of Airline Schedule Development 315 The Airline Operations Control Center (OCC) 3 320 4 Analysis of Operational Problems 331 5 Areas For Improvement 352 6 Case Study: PT Garuda Indonesia Airlines 357 REFERENCES 368 12 THE COMPLEX CONFIGURATION MODEL Bruce W. Patty and Jim Diamond 370 1 Introduction 370 Problem Description 2 371 Problem Formulation 3 375 4 Model Implementation 379 ix Contents 383 5 Summary REFERENCES 383 13 INTEGRATED AIRLINE SCHEDULE PLANNING Cynthia Barnhart, Fang Lu, and Rajesh Shenoi 384 1 Introduction 385 2 Fleet Assignment and Crew Pairing Problems: Existing M- els and Algorithms 388 3 An Integrated Approximate Fleet Assignment and Crew Pa- ing Model 393 4 An Advanced Integrated Solution Approach 395 5 Case Study 396 6 Conclusions and Future Research Directions 399 REFERENCES 401 14 AIRLINE SCHEDULE PERTURBATION PROBLEM: LANDING AND TAKEOFF WITH

With the emergence of smart technology and automated systems in today’s world, artificial intelligence (AI) is being incorporated into an array of professions. The aviation and aerospace industry, specifically, is a field that has seen the successful implementation of early stages of automation in daily flight operations through flight management systems and autopilot. However, the effectiveness of aviation systems and the provision of flight safety still depend primarily upon the reliability of aviation specialists and human decision making. The Handbook of Research on Artificial Intelligence Applications in the Aviation and Aerospace Industries is a pivotal reference source that explores best practices for AI implementation in aviation to enhance security and the ability to learn, improve, and predict. While highlighting topics such as computer-aided design, automated systems, and human factors, this publication explores the enhancement of global aviation security as well as the methods of modern information systems in the aeronautics industry. This book is ideally designed for pilots, scientists, engineers, aviation operators, air crash investigators, teachers, academicians, researchers, and students seeking current research on the application of AI in the field of aviation.