An Introduction to Optimization, Fourth Edition, Chong

Автор: Chong, Edwin K. P., Lu, Wu-sheng Zak, Stanislaw H.
Название: An Introduction to optimization
ISBN: 1119877636 ISBN-13(EAN): 9781119877639
Издательство: Wiley
Цена: 15840.00 р.
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Автор: Hazan, Elad
Название: Introduction to online convex optimization, second edition
ISBN: 0262046989 ISBN-13(EAN): 9780262046985
Издательство: Random House (USA)
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Описание: The Diesel That Did It tells the story of the legendary diesel-electric locomotive, the FT.

Автор: Diwekar Urmila M.
Название: Introduction to Applied Optimization
ISBN: 3030554066 ISBN-13(EAN): 9783030554064
Издательство: Springer
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Цена: 6097.00 р.
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Описание: 1. Introduction.- 2. Linear Programming.- 3. Nonlinear Programming.-4. Discrete Optimization.- 5. Optimization Under Uncertainty.- 6. Multiobjective Optimization.- 7.Optimal Control and Dynamic Optimization.- Index.

Автор: Du, Ding-zhu Pardalos, Panos M. Hu, Xiaodong Wu, Weili
Название: Introduction to combinatorial optimization
ISBN: 3031116844 ISBN-13(EAN): 9783031116841
Издательство: Springer
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Описание: Introductory courses in combinatorial optimization are popular at the upper undergraduate/graduate levels in computer science, industrial engineering, and business management/OR, owed to its wide applications in these fields. There are several published textbooks that treat this course and the authors have used many of them in their own teaching experiences. This present text fills a gap and is organized with a stress on methodology and relevant content, providing a step-by-step approach for the student to become proficient in solving combinatorial optimization problems. Applications and problems are considered via recent technology developments including wireless communication, cloud computing, social networks, and machine learning, to name several, and the reader is led to the frontiers of combinatorial optimization. Each chapter presents common problems, such as minimum spanning tree, shortest path, maximum matching, network flow, set-cover, as well as key algorithms, such as greedy algorithm, dynamic programming, augmenting path, and divide-and-conquer. Historical notes, ample exercises in every chapter, strategically placed graphics, and an extensive bibliography are amongst the gems of this textbook.

Автор: Diwekar, Urmila M.
Название: Introduction to applied optimization
ISBN: 3030554031 ISBN-13(EAN): 9783030554033
Издательство: Springer
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Описание: Optimization has pervaded all spheres of human endeavor. Although op- mization has been practiced in some form or other from the early prehistoric era, this area has seen progressive growth during the last ?ve decades. M- ern society lives not only in an environment of intense competition but is also constrained to plan its growth in a sustainable manner with due concern for conservation of resources. Thus, it has become imperative to plan, design, operate, and manage resources and assets in an optimal manner. Early - proaches have been to optimize individual activities in a standalone manner, however, thecurrenttrendistowardsanintegratedapproach: integratings- thesis and design, design and control, production planning, scheduling, and control. The functioning of a system may be governed by multiple perf- mance objectives. Optimization of such systems will call for special strategies for handling the multiple objectives to provide solutions closer to the systems requirement. Uncertainty and variability are two issues which render op- mal decision making di?cult. Optimization under uncertainty would become increasingly important if one is to get the best out of a system plagued by uncertain components. These issues have thrown up a large number of ch- lenging optimization problems which need to be resolved with a set of existing and newly evolving optimization tools. Optimization theory had evolved initially to provide generic solutions to optimizationproblemsinlinear, nonlinear, unconstrained, andconstrained- mains. Theseoptimization problems wereoften called mathematical progr- mingproblemswithtwodistinctiveclassi?cations, namelylinearandnonlinear programming pro

Автор: Treiber, Marco Alexander
Название: Optimization for computer vision
ISBN: 1447152824 ISBN-13(EAN): 9781447152828
Издательство: Springer
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Цена: 14635.00 р.
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Описание: Optimization for Computer Vision

Автор: Ferenc Forg?; Jeno Sz?p; Ferenc Szidarovszky
Название: Introduction to the Theory of Games
ISBN: 0792357752 ISBN-13(EAN): 9780792357759
Издательство: Springer
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Цена: 26711.00 р.
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Описание: Game theory is a collection of mathematical models designed for the analysis of strategic aspects of situations of conflict and cooperation in a broad spectrum of fields including economics and engineering. This book, places emphasis on methods of determining "solutions" of various game models.

Автор: Jahn Johannes
Название: Introduction to the Theory of Nonlinear Optimization
ISBN: 3030427595 ISBN-13(EAN): 9783030427597
Издательство: Springer
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Цена: 10976.00 р.
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Описание: This book serves as an introductory text to optimization theory in normed spaces and covers all areas of nonlinear optimization. It presents fundamentals with particular emphasis on the application to problems in the calculus of variations, approximation and optimal control theory.

Автор: Vazquez Alvarez Antonio Jose, Erwin Richard Scott
Название: An Introduction to Optimal Satellite Range Scheduling
ISBN: 3319797859 ISBN-13(EAN): 9783319797854
Издательство: Springer
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Цена: 6097.00 р.
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Описание: The satellite range scheduling (SRS) problem, an important operations research problem in the aerospace industry consisting of allocating tasks among satellites and Earth-bound objects, is examined in this book.

Автор: Peter Zornig
Название: Nonlinear Programming: An Introduction
ISBN: 3110315270 ISBN-13(EAN): 9783110315271
Издательство: Walter de Gruyter
Цена: 9288.00 р.
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Описание:

This book is an introduction to nonlinear programming. It deals with the theoretical foundations and solution methods, beginning with the classical procedures and reaching up to -modern- methods like trust region methods or procedures for nonlinear and global optimization. A comprehensive bibliography including diverse web sites with information about nonlinear programming, in particular software, is presented. Without sacrificing the necessary mathematical rigor, excessive formalisms are avoided. Several examples, exercises with detailed solutions, and applications are provided, making the text adequate for individual studies.

Автор: Adil Bagirov; Napsu Karmitsa; Marko M. M?kel?
Название: Introduction to Nonsmooth Optimization
ISBN: 331934627X ISBN-13(EAN): 9783319346274
Издательство: Springer
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Цена: 15855.00 р.
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Описание: This book is the first easy-to-read text on nonsmooth optimization (NSO, not necessarily differentiable optimization). The book covers both the theory and the numerical methods used in NSO and provide an overview of different problems arising in the field. a guide to NSO software.The book is ideal for anyone teaching or attending NSO courses.

Автор: Allaire, Gregoire (ecole Polytechnique, France)
Название: Numerical analysis and optimization
ISBN: 0199205213 ISBN-13(EAN): 9780199205219
Издательство: Oxford Academ
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Цена: 23879.00 р.
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Описание: This text, based on the author`s teaching at Ecole Polytechnique, introduces the reader to the world of mathematical modelling and numerical simulation. Including numerous exercises and examples, this is an ideal text for advanced students in Applied Mathematics, Engineering, Physical Science and Computer Science.

Автор: Nicolas Boumal
Название: An Introduction to Optimization on Smooth Manifolds
ISBN: 1009166158 ISBN-13(EAN): 9781009166157
Издательство: Cambridge Academ
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Цена: 6653.00 р.
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Описание: Optimization on Riemannian manifolds-the result of smooth geometry and optimization merging into one elegant modern framework-spans many areas of science and engineering, including machine learning, computer vision, signal processing, dynamical systems and scientific computing. This text introduces the differential geometry and Riemannian geometry concepts that will help students and researchers in applied mathematics, computer science and engineering gain a firm mathematical grounding to use these tools confidently in their research. Its charts-last approach will prove more intuitive from an optimizer's viewpoint, and all definitions and theorems are motivated to build time-tested optimization algorithms. Starting from first principles, the text goes on to cover current research on topics including worst-case complexity and geodesic convexity. Readers will appreciate the tricks of the trade for conducting research and for numerical implementations sprinkled throughout the book.