Solving Network Design Problems Via Decomposition Aggregation And Approximation
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Solving Network Design Problems via Decomposition, Aggregation and Approximation
Andreas Bärmann develops novel approaches for the solution of network design problems as they arise in various contexts of applied optimization. At the example of an optimal expansion of the German railway network until 2030, the author derives a tailor-made decomposition technique for multi-period network design problems. Next, he develops a general framework for the solution of network design problems via aggregation of the underlying graph structure. This approach is shown to save much computation time as compared to standard techniques. Finally, the author devises a modelling framework for the approximation of the robust counterpart under ellipsoidal uncertainty, an often-studied case in the literature. Each of these three approaches opens up a fascinating branch of research which promises a better theoretical understanding of the problem and an increasing range of solvable application settings at the same time.
Operations Research Proceedings 2016
This book includes a selection of refereed papers presented at the "Annual International Conference of the German Operations Research Society (OR2016)," which took place at the Helmut-Schmidt-Universität / Universität der Bundeswehr Hamburg, Germany, Aug. 30 - Sept. 2, 2016. Over 700 practitioners and academics from mathematics, computer science, business/economics, and related fields attended the conference. The scientific program included around 475 presentations on the theme Analytical Decision Making, focusing on the process of researching complex decision problems and devising effective solution methods towards better decisions. The book presents papers discussing classical mathematical optimization, statistics and simulation techniques. Such approaches are complemented by computer science methods and tools for the processing of data and the design and implementation of information systems. The book also examines recent advances in information technology, which allow big data volumes to be treated and enable real-time predictive and prescriptive business analytics to drive decisions and actions. Further, it includes problems modeled and treated under consideration of uncertainty, risk management, behavioral issues, and strategic decision situations.
Transportation and Traffic Theory 2009: Golden Jubilee
Author: William H. K. Lam
language: en
Publisher: Springer Science & Business Media
Release Date: 2009-09-01
th It is our great privilege and honor to present the proceedings of the 18 International Symposium on Transportation and Traffic Theory (ISTTT), held at The Hong Kong Polytechnic University in Hong Kong, China on 16-18 July 2009. th The 18 ISTTT is jointly organized by the Hong Kong Society for Transportation Studies and Department of Civil and Structural Engineering of The Hong Kong Polytechnic University. The ISTTT series is the main gathering for the world’s transportation and traffic theorists, and those who are interested in contributing to or gaining a deep understanding of traffic and transportation phenomena in order to better plan, design and manage the transportation system. Although it embraces a wide range of topics, from traffic flow theories and demand modeling to road safety and logistics and supply chain modeling, the ISTTT is hallmarked by its intellectual innovation, research and development excellence in the treatment of real-world transportation and traffic problems. The ISTTT prides itself in the extremely high quality of its proceedings. Previous ISTTT conferences were held in Warren, Michigan (1959), London (1963), New York (1965), Karlsruhe (1968), Berkeley, California (1971), Sydney (1974), Kyoto (1977), Toronto (1981), Delft (1984), Cambridge, Massachusetts (1987), Yokohama (1990), Berkeley, California (1993), Lyon (1996), Jerusalem (1999), Adelaide (2002), College Park, Maryland (2005), and London (2007). th th This 18 ISTTT celebrates the 50 Anniversary of this premier conference series.