Solution Methods for Robust Pricing for Transportation Networks Under Demand Uncertainty PDF Download
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Author: Lauren Marie Gardner
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Lauren Marie Gardner
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Stephen David Boyles
Publisher:
ISBN:
Category : Congestion pricing
Languages : en
Pages : 58
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Author: Joseph Ying Jun Chow
Publisher:
ISBN: 9781109678178
Category :
Languages : en
Pages : 256
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Book Description
Strategies, models, and algorithms facilitating such models are explored to provide transportation network managers and planners with more flexibility under uncertainty. Network design problems with non-stationary stochastic OD demand are formulated as real option investment problems and dynamic programming solution methodologies are used to obtain the value of flexibility to defer and re-design a network. The design premium is shown to reflect the opportunity cost of committing to a "preferred alternative" in transportation planning. Both network option and link option design problems are proposed with solution algorithms and tested on the classical Sioux Falls, SD network. Results indicate that allowing individual links to be deferred can have significant option value. A resource relocation model using non-stationary stochastic variables as chance constraints is proposed. The model is applied to air tanker relocation for initial attack of wildfires in California, and results show that the flexibility to switch locations with non-stationary stochastic variables providing 3-day or 7-day forecasts is more cost-effective than relocations without forecasting. Due to the computational costs of these more complex network models, a faster converging heuristic based on radial basis functions is evaluated for continuous network design problems for the Anaheim, CA network with a 31-dimensional decision variable. The algorithm is further modified and then proven to converge for multi-objective problems. Compared to other popular multi-objective solution algorithms in the literature such as the genetic algorithm, the proposed multi-objective radial basis function algorithm is shown to be most effective. The algorithm is applied to a flexible robust toll pricing problem, where toll pricing is proposed as a strategy to manage network robustness over multiple regimes of link capacity uncertainty. A link degradation simulation model is proposed that uses multivariate Bernoulli random variables to simulate correlated link failures. The solution to a multi-objective mean-variance toll pricing problem is obtained for the Sioux Falls network under low and high probability seasons, showing that the flexibility to adapt the Pareto set of toll solutions to changes in regime - e.g. hurricane seasons, security threat levels, etc - can increase value in terms of an epsilon indicator.
Author: David Levinson
Publisher: Springer Science & Business Media
ISBN: 1461409470
Category : Political Science
Languages : en
Pages : 263
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Book Description
This book contains selected peer-reviewed papers that were presented at the Fourth International Symposium on Transportation Network Reliability (INSTR) Conference held at the University of Minnesota July 22-23, 2010. International scholars, from a variety of disciplines--engineering, economics, geography, planning and transportation—offer varying perspectives on modeling and analysis of the reliability of transportation networks in order to illustrate both vulnerability to day-to-day and unpredictability variability and risk in travel, and demonstrates strategies for addressing those issues. The scope of the chapters includes all aspects of analysis and design to improve network reliability, specifically user perception of unreliability of public transport, public policy and reliability of travel times, the valuation and economics of reliability, network reliability modeling and estimation, travel behavior and vehicle routing under uncertainty, and risk evaluation and management for transportation networks. The book combines new methodologies and state of the art practice to model and address questions of network unreliability, making it of interest to both academics in transportation and engineering as well as policy-makers and practitioners.
Author: Jennifer Clare Duthie
Publisher:
ISBN:
Category : Origin and destination traffic surveys
Languages : en
Pages : 62
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Author: Fernando Ordóñez
Publisher:
ISBN:
Category : Highway capacity
Languages : en
Pages : 90
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Author: Saïd Salhi
Publisher: Springer Nature
ISBN: 3030969355
Category : Business & Economics
Languages : en
Pages : 923
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Book Description
Operations Research (OR) is a fast-evolving field, which is having a significant impact on its neighbouring disciplines of Business Analytics and Data Science, and on contemporary business and management practices. This handbook provides a comprehensive and cutting edge collection of studies in the area. Views differ on what should be included within the scope of OR. The editors of this volume have taken the view that an inclusive stance is the most helpful, both for theory and practice. Real-world problems often require consideration from both ‘softer’ and ‘harder’ perspectives and need consideration of both predictive and prescriptive problems. In accordance with this inclusive approach to OR, the book is divided into six parts, covering Discrete Optimization, Continuous Optimization, Heuristic Search Optimization, Forecasting, Simulation and Prediction, Problem Structuring and Behavioural OR, and finally some recent OR Applications. This wide-ranging handbook includes a culturally diverse collection of authors, with different perspectives and backgrounds around Operations Research. It will be of tremendous value to researchers, students and practitioners in the field of OR
Author: Xiang Li
Publisher: Springer Nature
ISBN: 9819999634
Category :
Languages : en
Pages : 474
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Author: Nikolaos Freris
Publisher: European Alliance for Innovation
ISBN: 1631904566
Category : Business & Economics
Languages : en
Pages : 822
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Book Description
The 2023 5th International Conference on Economic Management and Model Engineering (ICEMME 2023) was held on November 17-19, 2023 in Beijing, China. The primary objective of this conference is to facilitate the exchange of ideas and knowledge among researchers, scholars, and practitioners in the field of economic management and modeling engineering. Through presentations, discussions, and networking opportunities, participants will have the chance to explore the latest advancements, methodologies, and best practices in these areas. The conference was focused on three main themes: Enterprise Economic Management and Market Mechanism Assessment; Data Statistical Analysis and Economic Forecasting; Industrial Structure Optimization and Economic Green Development. For readers, this collection of papers offers a comprehensive insight into cutting-edge research and case studies, providing valuable information on current trends, challenges, and opportunities in economic management and modeling engineering. Readers will benefit from the diverse perspectives and innovative approaches presented in these papers, inspiring new ideas and solutions for their own research endeavors. Moreover, the positive influence of this conference extends beyond the current discussions. It is expected that the findings and recommendations shared in these proceedings will serve as a foundation for future research in the field of economic management and modeling engineering. By fostering collaboration, knowledge sharing, and academic discourse, this conference aims to contribute to the advancement of the field and stimulate further research initiatives in the years to come.
Author: Satish V. Ukkusuri
Publisher: Springer Science & Business Media
ISBN: 1461462436
Category : Business & Economics
Languages : en
Pages : 322
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Book Description
This edited book focuses on recent developments in Dynamic Network Modeling, including aspects of route guidance and traffic control as they relate to transportation systems and other complex infrastructure networks. Dynamic Network Modeling is generally understood to be the mathematical modeling of time-varying vehicular flows on networks in a fashion that is consistent with established traffic flow theory and travel demand theory. Dynamic Network Modeling as a field has grown over the last thirty years, with contributions from various scholars all over the field. The basic problem which many scholars in this area have focused on is related to the analysis and prediction of traffic flows satisfying notions of equilibrium when flows are changing over time. In addition, recent research has also focused on integrating dynamic equilibrium with traffic control and other mechanism designs such as congestion pricing and network design. Recently, advances in sensor deployment, availability of GPS-enabled vehicular data and social media data have rapidly contributed to better understanding and estimating the traffic network states and have contributed to new research problems which advance previous models in dynamic modeling. A recent National Science Foundation workshop on “Dynamic Route Guidance and Traffic Control” was organized in June 2010 at Rutgers University by Prof. Kaan Ozbay, Prof. Satish Ukkusuri , Prof. Hani Nassif, and Professor Pushkin Kachroo. This workshop brought together experts in this area from universities, industry and federal/state agencies to present recent findings in this area. Various topics were presented at the workshop including dynamic traffic assignment, traffic flow modeling, network control, complex systems, mobile sensor deployment, intelligent traffic systems and data collection issues. This book is motivated by the research presented at this workshop and the discussions that followed.
