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230201 ||| eng |
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|a 9783031124440
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|a Gkiotsalitis, Konstantinos
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| 245 |
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|a Public Transport Optimization
|h Elektronische Ressource
|c by Konstantinos Gkiotsalitis
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| 250 |
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|a 1st ed. 2022
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2022, 2022
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| 300 |
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|a XX, 626 p. 136 illus., 13 illus. in color
|b online resource
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| 505 |
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|a 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
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| 653 |
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|a Transportation engineering
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| 653 |
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|a Business logistics
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| 653 |
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|a Industrial Management
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| 653 |
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|a Operations Research, Management Science
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| 653 |
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|a Traffic engineering
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| 653 |
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|a Operations research
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| 653 |
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|a Management science
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| 653 |
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|a Supply Chain Management
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Transportation Technology and Traffic Engineering
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| 653 |
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|a Logistics
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 028 |
5 |
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|a 10.1007/978-3-031-12444-0
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-031-12444-0?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 658.7
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| 520 |
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|a 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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