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Public transport optimization

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Public transport optimizationby Konstantinos Gkiotsalitis.
作者:	Gkiotsalitis, Konstantinos.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	xx, 626 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	TransportationMathematical models.
電子資源:	https://doi.org/10.1007/978-3-031-12444-0
ISBN:	9783031124440$q(electronic bk.)

Public transport optimization
Gkiotsalitis, Konstantinos.

Public transport optimization[electronic resource] /by Konstantinos Gkiotsalitis. - Cham :Springer International Publishing :2022. - xx, 626 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783031124440$q(electronic bk.)

Standard No.: 10.1007/978-3-031-12444-0doiSubjects--Topical Terms:

338104
Transportation
--Mathematical models.

LC Class. No.: HE147.7 / .G55 2022

Dewey Class. No.: 388.015118

Public transport optimization
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505 0 $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.
520 $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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