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The book covers both theory and applications of locational analysis (LocAn). The reader will see the power of LocAn models in various real-world contexts, varying from communication design to robotics and mail delivery. It is divided into two parts. The first part contains an overview of some of the LocAn methodologies. The second part describes in thorough detail some selected applications. The text provides researchers with an excellent and well thought-out review of available location models.
Contains papers presented at a workshop held at The Fields Institute in May 1996. Papers are arranged in sections on theory, applications, and algorithms. Specific topics include testing the feasibility of semidefinite programs, semidefinite programming and graph equipartition, the totally nonnegative completion problem, approximation clustering, and cutting plane algorithms for semidefinite relaxations. For graduate students and researchers in mathematics, computer science, engineering, and operations. No index. Annotation copyrighted by Book News, Inc., Portland, OR
Detailed review of optimization from first principles, supported by rigorous math and computer science explanations and various learning aids Supported by rigorous math and computer science foundations, Combinatorial and Algorithmic Mathematics: From Foundation to Optimization provides a from-scratch understanding to the field of optimization, discussing 70 algorithms with roughly 220 illustrative examples, 160 nontrivial end-of-chapter exercises with complete solutions to ensure readers can apply appropriate theories, principles, and concepts when required, and Matlab codes that solve some specific problems. This book helps readers to develop mathematical maturity, including skills such as ...
This book contains a selection of papers presented at the conference on High Performance Software for Nonlinear Optimization (HPSN097) which was held in Ischia, Italy, in June 1997. The rapid progress of computer technologies, including new parallel architec tures, has stimulated a large amount of research devoted to building software environments and defining algorithms able to fully exploit this new computa tional power. In some sense, numerical analysis has to conform itself to the new tools. The impact of parallel computing in nonlinear optimization, which had a slow start at the beginning, seems now to increase at a fast rate, and it is reasonable to expect an even greater acceleration ...
In 1958, Ralph E. Gomory transformed the field of integer programming when he published a paper that described a cutting-plane algorithm for pure integer programs and announced that the method could be refined to give a finite algorithm for integer programming. In 2008, to commemorate the anniversary of this seminal paper, a special workshop celebrating fifty years of integer programming was held in Aussois, France, as part of the 12th Combinatorial Optimization Workshop. It contains reprints of key historical articles and written versions of survey lectures on six of the hottest topics in the field by distinguished members of the integer programming community. Useful for anyone in mathematics, computer science and operations research, this book exposes mathematical optimization, specifically integer programming and combinatorial optimization, to a broad audience.
Consisting of two parts, this book presents papers describing publicly available stochastic programming systems that are operational. It presents a diverse collection of application papers in areas such as production, supply chain and scheduling, gaming, environmental and pollution control, financial modeling, telecommunications, and electricity.
This book constitutes the refereed proceedings of the 12th Annual European Symposium on Algorithms, ESA 2004, held in Bergen, Norway, in September 2004. The 70 revised full papers presented were carefully reviewed from 208 submissions. The scope of the papers spans the entire range of algorithmics from design and mathematical issues to real-world applications in various fields, and engineering and analysis of algorithms.
This title is written in honor of Manfred Padberg, who has made fundamental contributions to both the theoretical and computational sides of integer programming and combinatorial optimization. This outstanding collection presents recent results in these areas that are closely connected to Padberg's research. His deep commitment to the geometrical approach to combinatorial optimization can be felt throughout this volume; his search for increasingly better and computationally efficient cutting planes gave rise to its title. The peer-reviewed papers contained here are based on invited lectures given at a workshop held in October 2001 to celebrate Padberg's 60th birthday. Grouped by topic (packing, stable sets, and perfect graphs; polyhedral combinatorics; general polytopes; semidefinite programming; computation), many of the papers set out to solve challenges set forth in Padberg's work. The book also shows how Padberg's ideas on cutting planes have influenced modern commercial optimization software.
LION 3, the Third International Conference on Learning and Intelligent Op- mizatioN, was held during January 14–18 in Trento, Italy. The LION series of conferences provides a platform for researchers who are interested in the int- section of e?cient optimization techniques and learning. It is aimed at exploring the boundaries and uncharted territories between machine learning, arti?cial intelligence, mathematical programming and algorithms for hard optimization problems. The considerable interest in the topics covered by LION was re?ected by the overwhelming number of 86 submissions, which almost doubled the 48 subm- sions received for LION’s second edition in December 2007. As in the ?rst two editions, the submissions to LION 3 could be in three formats: (a) original novel and unpublished work for publication in the post-conference proceedings, (b) extended abstracts of work-in-progressor a position statement, and (c) recently submitted or published journal articles for oral presentations. The 86 subm- sions received include 72, ten, and four articles for categories (a), (b), and (c), respectively.
In model predictive control (MPC) an optimization problem has to be solved at each time step, which in real-time applications makes it important to solve these efficiently and to have good upper bounds on worst-case solution time. Often for linear MPC problems, the optimization problem in question is a quadratic program (QP) that depends on parameters such as system states and reference signals. A popular class of methods for solving such QPs is active-set methods, where a sequence of linear systems of equations is solved. The primary contribution of this thesis is a method which determines which sequence of subproblems a popular class of such active-set algorithms need to solve, for every p...