Download Free Optimization Of Large Traffic Systems Book in PDF and EPUB Free Download. You can read online Optimization Of Large Traffic Systems and write the review.

This proceedings book presents the latest research findings, and theoretical and practical perspectives on innovative methods and development techniques related to the emerging areas of Web computing, intelligent systems and Internet computing. The Web has become an important source of information, and techniques and methodologies that extract quality information are of paramount importance for many Web and Internet applications. Data mining and knowledge discovery play a key role in many of today's major Web applications, such as e-commerce and computer security. Moreover, Web services provide a new platform for enabling service-oriented systems. The emergence of large-scale distributed computing paradigms, such as cloud computing and mobile computing systems, has opened many opportunities for collaboration services, which are at the core of any information system. Artificial intelligence (AI) is an area of computer science that builds intelligent systems and algorithms that work and react like humans. AI techniques and computational intelligence are powerful tools for learning, adaptation, reasoning and planning, and they have the potential to become enabling technologies for future intelligent networks. Research in the field of intelligent systems, robotics, neuroscience, artificial intelligence and cognitive sciences is vital for the future development and innovation of Web and Internet applications. Chapter "An Event-Driven Multi Agent System for Scalable Traffic Optimization" is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Scheduled transportation networks give rise to very complex and large-scale networkoptimization problems requiring innovative solution techniques and ideas from mathematical optimization and theoretical computer science. Examples of scheduled transportation include bus, ferry, airline, and railway networks, with the latter being a prime application domain that provides a fair amount of the most complex and largest instances of such optimization problems. Scheduled transport optimization deals with planning and scheduling problems over several time horizons, and substantial progress has been made for strategic planning and scheduling problems in all transportation domains. This state-of-the-art survey presents the outcome of an open call for contributions asking for either research papers or state-of-the-art survey articles. We received 24 submissions that underwent two rounds of the standard peer-review process, out of which 18 were finally accepted for publication. The volume is organized in four parts: Robustness and Recoverability, Robust Timetabling and Route Planning, Robust Planning Under Scarce Resources, and Online Planning: Delay and Disruption Management.
In this thesis, we propose novel computationally efficient optimization algorithms that derive effective traffic management strategies to reduce congestion and improve the efficiency of urban transportation systems. The proposed algorithms enable the use of high-resolution yet computationally inefficient urban traffic simulators to address large-scale urban transportation optimization problems in a computationally efficient manner. The first and the second part of this thesis focus on large-scale offline transportation optimization problems with stochastic simulation-based objective functions, analytical differentiable constraints and high-dimensional decision variables. We propose two optimization algorithms to solve these problems. In the first part, we propose a simulation-based metamodel algorithm that combines the use of an analytical stationary traffic network model and a dynamic microscopic traffic simulator. In the second part, we propose a metamodel algorithm that combines the use of an analytical transient traffic network model and the microscopic simulator. In the first part, we use the first metamodel algorithm to solve a large-scale fixed-time traffic signal control problem of the Swiss city of Lausanne with limited simulation runs, showing that the proposed algorithm can derive signal plans that outperform traditional simulation-based optimization algorithms and a commercial traffic signal optimization software. In the second part, we use both algorithms to solve a time-dependent traffic signal control problem of Lausanne, showing that the metamodel with the transient analytical traffic model outperforms that with the stationary traffic model. The third part of this thesis focuses on large-scale online transportation problems, which need to be solved with limited computational time. We propose a new optimization framework that combines the use of a problem-specific model-driven method, i.e., the method proposed in the first part, with a generic data-driven supervised machine learning method. We use this framework to address a traffic responsive control problem of Lausanne. We compare the performance of the proposed framework with the performance of an optimization framework with only the model-driven method and an optimization framework with only the data-driven method, showing that the proposed framework is able to derive signal plans that outperform the signal plans derived by the other two frameworks in most cases.
Transportation systems in buildings are part of everyday life: whether ferrying people twenty storeys up to the office or moving luggage at the airport, 21st-century society relies on them. This book presents the latest in analysis and control of transportation systems in buildings focusing primarily on elevator groups. The theory and design of passenger and cargo transport systems are covered, with operational examples and topics of special interest.
This volume provides resourceful thinking and insightful management solutions to the many challenges that decision makers face in their predictions, preparations, and implementations of the key elements that our societies and industries need to take as they move toward digitalization and smartness. The discussions within the book aim to uncover the sources of large-scale problems in socio-industrial dilemmas, and the theories that can support these challenges. How theories might also transition to real applications is another question that this book aims to uncover. In answer to the viewpoints expressed by several practitioners and academicians, this book aims to provide both a learning platform which spotlights open questions with related case studies. The relationship between Industry 4.0 and Society 5.0 provides the basis for the expert contributions in this book, highlighting the uses of analytical methods such as mathematical optimization, heuristic methods, decomposition methods, stochastic optimization, and more. The book will prove useful to researchers, students, and engineers in different domains who encounter large scale optimization problems and will encourage them to undertake research in this timely and practical field. The book splits into two parts. The first part covers a general perspective and challenges in a smart society and in industry. The second part covers several case studies and solutions from the operations research perspective for large scale challenges specific to various industry and society related phenomena.
Technical, Commerical and Regulatory Challenges of QoS provides a comprehensive examination of Internet QoS theory, standards, vendor implementation and network deployment from the practitioner's point of view, including extensive discussion of related economic and regulatory issues. Written in a technology-light way so that a variety of professionals and researchers in the information and networking industries can easily grasp the material. Includes case studies based on real-world experiences from industry. The author starts by discussing the economic, regulatory and technical challenges of the existing QoS model. Key coverage includes defining a clear business model for selling and buying QoS in relation to current and future direction of government regulation and QoS interoperability (or lack thereof) between carriers and networking devices. The author then demonstrates how to improve the current QoS model to create a clear selling point, less regulation uncertainty, and higher chance of deployment success. This includes discussion of QoS re-packaging to end-users; economic and regulatory benefits of the re-packaging; and the overall benefits of an improved technical approach. Finally, the author discusses the future evolution of QoS from an Internet philosophy perspective and lets the reader draw the conclusions. This book is the first QoS book to provide in depth coverage on the commercial and regulatory aspects of QoS, in addition to the technical aspect. From that, readers can grasp the commercial and regulatory issues of QoS and their implications on the overall QoS business model. This book is also the first QoS book to provide case studies of real world QoS deployments, contributed by the people who did the actual deployments. From that, readers can grasp the practical issues of QoS in real world. This book is also the first QoS book to cover both wireline QoS and wireless QoS. Readers can grasp the QoS issues in the wireless world. The book was reviewed and endorsed by a long list of prominent industrial and academic figures. Discusses QoS technology in relation to economic and regulatory issues Includes case studies based on real-world examples from industry practitioners Provides unique insight into how to improve the current QoS model to create a clear selling point, less regulatory uncertainty, and higher chance of deployment success
Part one looks at delay-tolerant network architectures and platforms including DTN for satellite communications and deep-space communications, underwater networks, networks in developing countries, vehicular networks and emergency communications. Part two covers delay-tolerant network routing, including issues such as congestion control, naming, addressing and interoperability. Part three explores services and applications in delay-tolerant networks, such as web browsing, social networking and data streaming. Part four discusses enhancing the performance, reliability, privacy and security of delay-tolerant networks. Chapters cover resource sharing, simulation and modeling and testbeds. Reviews the different types of DTN and shows how they can be applied in satellite and deep-space communications, vehicular and underwater communications, and during large-scale disasters Considers the potential for rapid selection and dissemination of urgent messages is considered Reviews the breadth of areas in which DTN is already providing solutions and the prospects for its wider adoption
This book is one of the first to include an extensive discussion of integrated public transport planning. In times of growing urban populations and increasing environmental awareness, the importance of optimizing public transport systems is ever-developing. Three different aspects are presented: line planning, timetabling, and vehicle scheduling. Classically, challenges concerning these three aspects of planning are solved sequentially. Due to their high interdependence, the author presents a clear and detailed analysis of innovative, integrated models with accompanied numerical experiments performed to assess, and often support, the benefits of integration. The book will appeal to a wide readership ranging from graduate students to researchers.
This book is focused on the discussion of the traffic assignment problem, the mathematical and practical meaning of variables, functions and basic principles. This work gives information about new approaches, methods and algorithms based on original methodological technique, developed by authors in their publications for the past several years, as well as corresponding prospective implementations. The book may be of interest to a wide range of readers, such as civil engineering students, traffic engineers, developers of traffic assignment algorithms etc. The obtained results here are to be used in both practice and theory. This book is devoted to the traffic assignment problem, formulated in a form of nonlinear optimization program. The most efficient solution algorithms related to the problem are based on its structural features and practical meaning rather than on standard nonlinear optimization techniques or approaches. The authors have carefully considered the meaning of the traffic assignment problem for efficient algorithms development.