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Optimization Theory for Large Systems

2013-01-17 Mathematics
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Release : 2013-01-17
Genre : Mathematics
Kind : eBook
Book Rating : 694/5 ( reviews)

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Book Synopsis Optimization Theory for Large Systems by : Leon S. Lasdon

Download or read book Optimization Theory for Large Systems written by Leon S. Lasdon. This book was released on 2013-01-17. Available in PDF, EPUB and Kindle. Book excerpt: Important text examines most significant algorithms for optimizing large systems and clarifying relations between optimization procedures. Much data appear as charts and graphs and will be highly valuable to readers in selecting a method and estimating computer time and cost in problem-solving. Initial chapter on linear and nonlinear programming presents all necessary background for subjects covered in rest of book. Second chapter illustrates how large-scale mathematical programs arise from real-world problems. Appendixes. List of Symbols.

Optimization Theory for Large Systems [by] Leon S. Lasdon

1970 Mathematical optimization
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Release : 1970
Genre : Mathematical optimization
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Optimization Theory for Large Systems [by] Leon S. Lasdon by : Leon S. Lasdon

Download or read book Optimization Theory for Large Systems [by] Leon S. Lasdon written by Leon S. Lasdon. This book was released on 1970. Available in PDF, EPUB and Kindle. Book excerpt:

Online Optimization of Large Scale Systems

2013-03-14 Mathematics
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Release : 2013-03-14
Genre : Mathematics
Kind : eBook
Book Rating : 319/5 ( reviews)

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Book Synopsis Online Optimization of Large Scale Systems by : Martin Grötschel

Download or read book Online Optimization of Large Scale Systems written by Martin Grötschel. This book was released on 2013-03-14. Available in PDF, EPUB and Kindle. Book excerpt: In its thousands of years of history, mathematics has made an extraordinary ca reer. It started from rules for bookkeeping and computation of areas to become the language of science. Its potential for decision support was fully recognized in the twentieth century only, vitally aided by the evolution of computing and communi cation technology. Mathematical optimization, in particular, has developed into a powerful machinery to help planners. Whether costs are to be reduced, profits to be maximized, or scarce resources to be used wisely, optimization methods are available to guide decision making. Opti mization is particularly strong if precise models of real phenomena and data of high quality are at hand - often yielding reliable automated control and decision proce dures. But what, if the models are soft and not all data are around? Can mathematics help as well? This book addresses such issues, e. g. , problems of the following type: - An elevator cannot know all transportation requests in advance. In which order should it serve the passengers? - Wing profiles of aircrafts influence the fuel consumption. Is it possible to con tinuously adapt the shape of a wing during the flight under rapidly changing conditions? - Robots are designed to accomplish specific tasks as efficiently as possible. But what if a robot navigates in an unknown environment? - Energy demand changes quickly and is not easily predictable over time. Some types of power plants can only react slowly.

Large-scale Optimization

2013-03-09 Computers
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Release : 2013-03-09
Genre : Computers
Kind : eBook
Book Rating : 430/5 ( reviews)

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Book Synopsis Large-scale Optimization by : Vladimir Tsurkov

Download or read book Large-scale Optimization written by Vladimir Tsurkov. This book was released on 2013-03-09. Available in PDF, EPUB and Kindle. Book excerpt: Decomposition methods aim to reduce large-scale problems to simpler problems. This monograph presents selected aspects of the dimension-reduction problem. Exact and approximate aggregations of multidimensional systems are developed and from a known model of input-output balance, aggregation methods are categorized. The issues of loss of accuracy, recovery of original variables (disaggregation), and compatibility conditions are analyzed in detail. The method of iterative aggregation in large-scale problems is studied. For fixed weights, successively simpler aggregated problems are solved and the convergence of their solution to that of the original problem is analyzed. An introduction to block integer programming is considered. Duality theory, which is widely used in continuous block programming, does not work for the integer problem. A survey of alternative methods is presented and special attention is given to combined methods of decomposition. Block problems in which the coupling variables do not enter the binding constraints are studied. These models are worthwhile because they permit a decomposition with respect to primal and dual variables by two-level algorithms instead of three-level algorithms. Audience: This book is addressed to specialists in operations research, optimization, and optimal control.

Large-Scale and Distributed Optimization

2018-11-11 Mathematics
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Release : 2018-11-11
Genre : Mathematics
Kind : eBook
Book Rating : 785/5 ( reviews)

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Book Synopsis Large-Scale and Distributed Optimization by : Pontus Giselsson

Download or read book Large-Scale and Distributed Optimization written by Pontus Giselsson. This book was released on 2018-11-11. Available in PDF, EPUB and Kindle. Book excerpt: This book presents tools and methods for large-scale and distributed optimization. Since many methods in "Big Data" fields rely on solving large-scale optimization problems, often in distributed fashion, this topic has over the last decade emerged to become very important. As well as specific coverage of this active research field, the book serves as a powerful source of information for practitioners as well as theoreticians. Large-Scale and Distributed Optimization is a unique combination of contributions from leading experts in the field, who were speakers at the LCCC Focus Period on Large-Scale and Distributed Optimization, held in Lund, 14th–16th June 2017. A source of information and innovative ideas for current and future research, this book will appeal to researchers, academics, and students who are interested in large-scale optimization.

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