Public Transport Optimization
Autor Konstantinos Gkiotsalitisen Limba Engleză Hardback – 21 ian 2023
This textbook provides a comprehensive step-by-step guide for new public transport modelers. It includes an introduction to mathematical modeling, continuous and discrete optimization, numerical optimization, computational complexity analysis, metaheuristics, and multi-objective optimization. These tools help engineers and modelers to use better existing public transport models and also develop new models that can address future challenges. By reading this book, the reader will gain the ability to translate a future problem description into a mathematical model and solve it using an appropriate solution method.
The textbook provides the knowledge needed to develop highly accurate mathematical models that can serve as decision support tools at the strategic, tactical, and operational planning levels of public transport services. Its detailed description of exact optimization methods, metaheuristics, bi-level, and multi-objective optimization approaches together with the detailed description of implementing these approaches in classic public transport problems with the use of open source tools is unique and will be highly useful to students and transport professionals.
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Specificații
ISBN-13: 9783031124433
ISBN-10: 303112443X
Pagini: 626
Ilustrații: XX, 626 p. 136 illus., 13 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1.08 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
ISBN-10: 303112443X
Pagini: 626
Ilustrații: XX, 626 p. 136 illus., 13 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 1.08 kg
Ediția:1st ed. 2022
Editura: Springer International Publishing
Colecția Springer
Locul publicării:Cham, Switzerland
Cuprins
Part I Mathematical Programming of Public Transport Problems.- 1 Introduction to Mathematical Programming.- 2 Introduction to Computational Complexity.- 3 Continuous Unconstrained Optimization.- 4 Continuous Constrained Optimization.- 5 Discrete Optimization.- Part II Solution Approximation with Artificial Intelligence: The case of metaheuristics.- 6 Metaheuristics for Discrete Optimization Problems.- 7 Metaheuristics for Continuous Optimization Problems.- 8 Multi-objective Optimization Metaheuristics.- Part III Public Transport Optimization: from Network Design to Operations.- 9 Public Transport Network Design.- 10 Tactical Planning of Public Transport Services.- 11 Multi-modal Synchronization at the Tactical Planning Stage.- 12 Operational Planning and Control.- 13 Planning under Uncertainty.
Notă biografică
Dr Konstantinos Gkiotsalitis is an Assistant Professor in data science in transportation engineering at the Transport Engineering and Management (TEM) group, Dept. of Civil Engineering, University of Twente. His research focuses on mathematical modeling and optimization in transport, with specific emphasis on public transport planning and operations. From 2012 until 2018, he was conducting industrial research related to public transport optimization at NEC Laboratories Europe (Heidelberg, Germany) with a specific focus on EU and APAC markets.
He received his PhD from the National Technical University of Athens on unveiling the mobility patterns of individuals and matching the public transportation supply with the travel demand. He also received his bachelor's degree in Civil Engineering from the National Technical University of Athens (2010) and his MSc in Transport and Sustainable Development from Imperial College London and University College London (2012).
He has been involved in several EU and international projects on smart cities, urban mobility, public transport operations, MaaS, and logistics, and he holds several patents in the aforementioned areas. He is also Review Coordinator of the Transit Management and Performance committee (AP010) at the Transportation Research Board, and he has served as guest editor on public transport-related special issues in scientific journals. He has authored more than 45 peer-reviewed scientific articles in international scientific journals in the area of public transport optimization and he has received the 2022 Best Paper Award in the highly impactful Transport Reviews journal.
Textul de pe ultima copertă
This textbook provides a comprehensive step-by-step guide for new public transport modelers. It includes an introduction to mathematical modeling, continuous and discrete optimization, numerical optimization, computational complexity analysis, metaheuristics, and multi-objective optimization. These tools help engineers and modelers to use better existing public transport models and also develop new models that can address future challenges. By reading this book, the reader will gain the ability to translate a future problem description into a mathematical model and solve it using an appropriate solution method.
The textbook provides the knowledge needed to develop highly accurate mathematical models that can serve as decision support tools at the strategic, tactical, and operational planning levels of public transport services. Its detailed description of exact optimization methods, metaheuristics, bi-level, and multi-objective optimization approaches together with the detailed description of implementing these approaches in classic public transport problems with the use of open source tools is unique and will be highly useful to students and transport professionals.
Caracteristici
Provides comprehensive training for the public transport modelers of future to enabling them to create their own models Includes information about optimization approaches, metaheuristics, and analysis of computational complexities Contains many examples, problems, and solutions to aid learning