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 develops models, results and algorithms for optimizing public transportation from a customer-oriented viewpoint. The methods used are based on graph-theoretic approaches and integer programming. The specific topics are all motivated by real-world examples which occurred in practical projects: location of stops, management of delay, and tariff zone design. An appendix summarizes some of the basics of optimization needed to interpret the material in the book.

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.

This book contains selected papers from the presentations given at the 7th EURO-Working Group Meeting on 'Iransportation, which took place at the Helsinki University of Technology (HUT), Finland, during August 2-4, 1999. Altogether 31 presentations were given and 14 full papers have been selected in this publication through a peer review process coordinated by the editors. The papers in this book cover a wide range of transportation problems from the simulation of railway traffic to optimum congestion tolling and mode choice modeling with stated preference data. In general, the variety of papers clearly demonstrates the wide areas of interest of people who are involved in the research of transportation systems and their operation. They as well demonstrate the importance and possibilities of modeling and theoretical approaches in the analysis of transportation systems and problem solving. Most of the papers are purely theoretical in nature, that is, they present a theoretical model with only a hypothetical example of applica tion. There are, however, some papers, which are closer to the practice or describe applications of and give interesting results of studies made by known methodologies. It is especially noteworthy, that half of the accepted papers deal with planning and operation of public transport.

This book contains selected papers from the presentations given at the 7th EURO-Working Group Meeting on 'Iransportation, which took place at the Helsinki University of Technology (HUT), Finland, during August 2-4, 1999. Altogether 31 presentations were given and 14 full papers have been selected in this publication through a peer review process coordinated by the editors. The papers in this book cover a wide range of transportation problems from the simulation of railway traffic to optimum congestion tolling and mode choice modeling with stated preference data. In general, the variety of papers clearly demonstrates the wide areas of interest of people who are involved in the research of transportation systems and their operation. They as well demonstrate the importance and possibilities of modeling and theoretical approaches in the analysis of transportation systems and problem solving. Most of the papers are purely theoretical in nature, that is, they present a theoretical model with only a hypothetical example of applica tion. There are, however, some papers, which are closer to the practice or describe applications of and give interesting results of studies made by known methodologies. It is especially noteworthy, that half of the accepted papers deal with planning and operation of public transport.

Efficient transfer between science and society is crucial for their future development. The rapid progress of information technology and computer systems offers a large potential and new perspectives for solving complex problems. Mathematical modelling and simulation have become important tools not only in scientific investigations but also in analysing, planning and controlling technological and economic processes. Mathematics, imbedded in an interdisciplinary concept, has become a key technology. The book covers the results of a variety of major projects in industrial mathematics following an initiative of the German Federal Ministry of Education and Research. All projects are collaborations of industrial companies and university-based researchers, and range from automotive industry to computer technology and medical visualisation. In general, the projects presented in this volume prove that new mathematical ideas and methods can be decisive for the solution of industrial and economic problems.

This book treats three planning problems arising in public railway transportation planning: line planning, timetabling, and delay management, with the objective to minimize passengers’ travel time. While many optimization approaches simplify these problems by assuming that passengers’ route choice is independent of the solution, this book focuses on models which take into account that passengers will adapt their travel route to the implemented planning solution. That is, a planning solution and passengers’ routes are determined and evaluated simultaneously. This work is technically deep, with insightful finding regarding complexity and algorithmic approaches to public transportation problems with integrated passenger routing. It is intended for researchers in the fields of mathematics, computer science, or operations research, working in the field of public transportation from an optimization standpoint. It is also ideal for students who want to gain intuition and experience in doing complexity proofs and designing polynomial-time algorithms for network problems. The book models line planning, timetabling and delay management as combined design and routing problems on networks. In a complexity analysis, the border between NP-hard and polynomially solvable problems is illustrated. Based on that, the insights gained are used to develop solution approaches for the considered problems. Besides integer programming formulations, a heuristic method iterating planning and routing step is proposed to solve the problems.

Public transportation is undeniably an effective way to move a large number of people in a city. Its ineffectiveness, such as long travel times, poor coverage, and lack of direct services, however, makes it unappealing to many commuters. In this thesis, we address some of the shortcomings and propose solutions for making public transportation more preferable. The first part of this thesis is focused on improving existing bus services to provide higher levels of service. We propose an optimization model to determine limited-stop service to be operated in parallel with local service to maximize total user welfare. Theoretical properties of the model are established and used to develop an efficient solution approach. We present numerical results obtained using real-world data and demonstrate the benefits of limited-stop services. The second part of this thesis concerns the design of integrated vehicle-sharing and public transportation services. One-way vehicle-sharing services can provide better access to existing public transportation and additional options for trips beyond those provided by public transit. The contributions of this part are twofold. First, we present a framework for evaluating the impacts of integrating one-way vehicles haring service with existing public transportation. Using publicly available data, we construct a graph representing a multi-modal transportation service. Various evaluation metrics based on centrality indices are proposed. Additionally, we introduce the notion of a transfer tree and develop a visualization tool that enables us to easily compare commuting patterns from different origins. The framework is applied to assess the impact of Hubway (a bike-sharing service) on public transportation service in the Boston metropolitan area. Second, we present an optimization model to select a subset of locations at which installing vehicle-sharing stations minimizes overall travel time over the integrated network. Benders decomposition is used to tackle large instances. While a tight formulation generally generates stronger Benders cuts, it requires a large number of variables and constraints, and hence, more computational effort. We propose new algorithms that produce strong Benders cuts quickly by aggregating various variables and constraints. Using data from the Boston metropolitan area, we present computational experiments that confirm the effectiveness of our solution approach.

Network optimization is important in the modeling of problems and processes from such fields as engineering, computer science, operations research, transportation, telecommunication, decision support systems, manufacturing, and airline scheduling. Recent advances in data structures, computer technology, and algorithm development have made it possible to solve classes of network optimization problems that until recently were intractable. The refereed papers in this volume reflect the interdisciplinary efforts of a large group of scientists from academia and industry to model and solve complicated large-scale network optimization problems.