Air Transport: A Computer Science Perspective

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Air Transport: A Computer Science Perspective is written by Sebastian Wandelt and published by Elsevier. It's available with International Standard Book Number or ISBN identification 0443451516 (ISBN 10) and 9780443451515 (ISBN 13).

Air Transport: A Computer Science Perspective thoroughly examines the integration of computer science principles in the field of air transportation. Bridging the gap between theory and real-world applications, it delves into automation, complex problem-solving, and cutting-edge technology in aviation. Authored by a seasoned team of a computer scientist and an airspace engineer, it offers a unique blend of expertise that highlights practical applications of algorithms, data structures, and optimization techniques essential for enhancing flight operations and enabling autonomous systems. Readers will gain insights into the latest regulatory frameworks, ensuring they are well-equipped to navigate the evolving air transport landscape.Structured in five parts, the book begins with foundational concepts such as computational complexity and intelligence. It then delves into critical aspects of airline operations, including network design, flight scheduling, fleet assignment, and aircraft routing. The exploration continues with airport operations, focusing on gate assignment, ground vehicle allocation, and delay prediction. In the realm of air traffic flow management, readers will discover trajectory optimization, airspace sectorization, and network resilience assessment. The concluding section summarizes key findings and provides an outlook on future advancements in the field.This book is an invaluable resource for a diverse audience, including transportation engineers, computer scientists eager to tackle real-world air transport challenges, and professionals in data science, software engineering, and aviation research. It is ideal for students in aerospace engineering, computer science, and data science programs, emphasizing practical applications that drive innovation and efficiency in the air transport sector. - Includes comprehensive, expert-curated reviews of the academic literature on each subject, providing readers with a solid foundation in the latest research and developments - Dedicates a significant portion to exploring modern computational intelligence techniques, such as machine learning, deep learning, and optimization algorithms, with a focus on their application in air transport, helping readers understand how to leverage them for innovative solutions - Explicitly addresses the computational complexity involved in real-world use cases, including algorithm efficiency, scalability, and the trade-offs between computational complexity and solution accuracy, providing readers with practical strategies for managing and overcoming these challenges