Classical and Modern Optimization

Classical and Modern Optimization PDF Author: Guillaume Carlier
Publisher: Advanced Textbooks in Mathemat
ISBN: 9781800610866
Category : Mathematics
Languages : en
Pages : 358

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Book Description
Topological and functional analytic preliminaries -- Differential calculus -- Convexity -- Optimality conditions for differentiable optimization -- Problems depending on a parameter -- Convex duality and applications -- Iterative methods for convex minimization -- When optimization and data meet -- An invitation to the calculus of variations.

Classical and Modern Optimization

Classical and Modern Optimization PDF Author: Guillaume Carlier
Publisher: Advanced Textbooks in Mathemat
ISBN: 9781800610866
Category : Mathematics
Languages : en
Pages : 358

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Book Description
Topological and functional analytic preliminaries -- Differential calculus -- Convexity -- Optimality conditions for differentiable optimization -- Problems depending on a parameter -- Convex duality and applications -- Iterative methods for convex minimization -- When optimization and data meet -- An invitation to the calculus of variations.

Handbook of Optimization

Handbook of Optimization PDF Author: Ivan Zelinka
Publisher: Springer Science & Business Media
ISBN: 3642305040
Category : Technology & Engineering
Languages : en
Pages : 1100

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Book Description
Optimization problems were and still are the focus of mathematics from antiquity to the present. Since the beginning of our civilization, the human race has had to confront numerous technological challenges, such as finding the optimal solution of various problems including control technologies, power sources construction, applications in economy, mechanical engineering and energy distribution amongst others. These examples encompass both ancient as well as modern technologies like the first electrical energy distribution network in USA etc. Some of the key principles formulated in the middle ages were done by Johannes Kepler (Problem of the wine barrels), Johan Bernoulli (brachystochrone problem), Leonhard Euler (Calculus of Variations), Lagrange (Principle multipliers), that were formulated primarily in the ancient world and are of a geometric nature. In the beginning of the modern era, works of L.V. Kantorovich and G.B. Dantzig (so-called linear programming) can be considered amongst others. This book discusses a wide spectrum of optimization methods from classical to modern, alike heuristics. Novel as well as classical techniques is also discussed in this book, including its mutual intersection. Together with many interesting chapters, a reader will also encounter various methods used for proposed optimization approaches, such as game theory and evolutionary algorithms or modelling of evolutionary algorithm dynamics like complex networks.

Optimization Theory with Applications

Optimization Theory with Applications PDF Author: Donald A. Pierre
Publisher: Courier Corporation
ISBN: 0486136957
Category : Mathematics
Languages : en
Pages : 640

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Book Description
Broad-spectrum approach to important topic. Explores the classic theory of minima and maxima, classical calculus of variations, simplex technique and linear programming, optimality and dynamic programming, more. 1969 edition.

Classical And Modern Optimization

Classical And Modern Optimization PDF Author: Guillaume Carlier
Publisher: World Scientific
ISBN: 180061067X
Category : Mathematics
Languages : en
Pages : 388

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Book Description
The quest for the optimal is ubiquitous in nature and human behavior. The field of mathematical optimization has a long history and remains active today, particularly in the development of machine learning.Classical and Modern Optimization presents a self-contained overview of classical and modern ideas and methods in approaching optimization problems. The approach is rich and flexible enough to address smooth and non-smooth, convex and non-convex, finite or infinite-dimensional, static or dynamic situations. The first chapters of the book are devoted to the classical toolbox: topology and functional analysis, differential calculus, convex analysis and necessary conditions for differentiable constrained optimization. The remaining chapters are dedicated to more specialized topics and applications.Valuable to a wide audience, including students in mathematics, engineers, data scientists or economists, Classical and Modern Optimization contains more than 200 exercises to assist with self-study or for anyone teaching a third- or fourth-year optimization class.

Classical and Recent Aspects of Power System Optimization

Classical and Recent Aspects of Power System Optimization PDF Author: Ahmed F. F. Zobaa
Publisher: Academic Press
ISBN: 0128124423
Category : Technology & Engineering
Languages : en
Pages : 586

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Book Description
Classical and Recent Aspects of Power System Optimization presents conventional and meta-heuristic optimization methods and algorithms for power system studies. The classic aspects of optimization in power systems, such as optimal power flow, economic dispatch, unit commitment and power quality optimization are covered, as are issues relating to distributed generation sizing, allocation problems, scheduling of renewable resources, energy storage, power reserve based problems, efficient use of smart grid capabilities, and protection studies in modern power systems. The book brings together innovative research outcomes, programs, algorithms and approaches that consolidate the present state and future challenges for power. Analyzes and compares several aspects of optimization for power systems which has never been addressed in one reference Details real-life industry application examples for each chapter (e.g. energy storage and power reserve problems) Provides practical training on theoretical developments and application of advanced methods for optimum electrical energy for realistic engineering problems

Modern Optimization Methods for Science, Engineering and Technology

Modern Optimization Methods for Science, Engineering and Technology PDF Author: G. R. Sinha
Publisher:
ISBN: 9780750324045
Category : Electronic books
Languages : en
Pages : 0

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Book Description
Achieving a better solution or improving the performance of existing system design is an ongoing a process for which scientists, engineers, mathematicians and researchers have been striving for many years. Ever increasingly practical and robust methods have been developed, and every new generation of computers with their increased power and speed allows for the development and wider application of new types of solutions. This book defines the fundamentals, background and theoretical concepts of optimization principles in a comprehensive manner along with their potential applications and implementation strategies. It encompasses linear programming, multivariable methods for risk assessment, nonlinear methods, ant colony optimization, particle swarm optimization, multi-criterion and topology optimization, learning classifier, case studies on six sigma, performance measures and evaluation, multi-objective optimization problems, machine learning approaches, genetic algorithms and quality of service optimizations. The book will be very useful for wide spectrum of target readers including students and researchers in academia and industry.

Handbook of Optimization

Handbook of Optimization PDF Author: Ivan Zelinka
Publisher: Springer Science & Business Media
ISBN: 3642305032
Category : Computers
Languages : en
Pages : 1088

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Book Description
Optimization problems were and still are the focus of mathematics from antiquity to the present. Since the beginning of our civilization, the human race has had to confront numerous technological challenges, such as finding the optimal solution of various problems including control technologies, power sources construction, applications in economy, mechanical engineering and energy distribution amongst others. These examples encompass both ancient as well as modern technologies like the first electrical energy distribution network in USA etc. Some of the key principles formulated in the middle ages were done by Johannes Kepler (Problem of the wine barrels), Johan Bernoulli (brachystochrone problem), Leonhard Euler (Calculus of Variations), Lagrange (Principle multipliers), that were formulated primarily in the ancient world and are of a geometric nature. In the beginning of the modern era, works of L.V. Kantorovich and G.B. Dantzig (so-called linear programming) can be considered amongst others. This book discusses a wide spectrum of optimization methods from classical to modern, alike heuristics. Novel as well as classical techniques is also discussed in this book, including its mutual intersection. Together with many interesting chapters, a reader will also encounter various methods used for proposed optimization approaches, such as game theory and evolutionary algorithms or modelling of evolutionary algorithm dynamics like complex networks.

Modern Portfolio Optimization with NuOPTTM, S-PLUS®, and S+BayesTM

Modern Portfolio Optimization with NuOPTTM, S-PLUS®, and S+BayesTM PDF Author: Bernd Scherer
Publisher: Springer Science & Business Media
ISBN: 038727586X
Category : Business & Economics
Languages : en
Pages : 422

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Book Description
In recent years portfolio optimization and construction methodologies have become an increasingly critical ingredient of asset and fund management, while at the same time portfolio risk assessment has become an essential ingredient in risk management. This trend will only accelerate in the coming years. This practical handbook fills the gap between current university instruction and current industry practice. It provides a comprehensive computationally-oriented treatment of modern portfolio optimization and construction methods using the powerful NUOPT for S-PLUS optimizer.

Optimization

Optimization PDF Author: Jan Brinkhuis
Publisher: Princeton University Press
ISBN: 1400829364
Category : Mathematics
Languages : en
Pages : 683

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Book Description
This self-contained textbook is an informal introduction to optimization through the use of numerous illustrations and applications. The focus is on analytically solving optimization problems with a finite number of continuous variables. In addition, the authors provide introductions to classical and modern numerical methods of optimization and to dynamic optimization. The book's overarching point is that most problems may be solved by the direct application of the theorems of Fermat, Lagrange, and Weierstrass. The authors show how the intuition for each of the theoretical results can be supported by simple geometric figures. They include numerous applications through the use of varied classical and practical problems. Even experts may find some of these applications truly surprising. A basic mathematical knowledge is sufficient to understand the topics covered in this book. More advanced readers, even experts, will be surprised to see how all main results can be grounded on the Fermat-Lagrange theorem. The book can be used for courses on continuous optimization, from introductory to advanced, for any field for which optimization is relevant.

Mathematics of Optimization: How to do Things Faster

Mathematics of Optimization: How to do Things Faster PDF Author: Steven J. Miller
Publisher: American Mathematical Soc.
ISBN: 1470441144
Category : Management science
Languages : en
Pages : 327

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Book Description
Optimization Theory is an active area of research with numerous applications; many of the books are designed for engineering classes, and thus have an emphasis on problems from such fields. Covering much of the same material, there is less emphasis on coding and detailed applications as the intended audience is more mathematical. There are still several important problems discussed (especially scheduling problems), but there is more emphasis on theory and less on the nuts and bolts of coding. A constant theme of the text is the “why” and the “how” in the subject. Why are we able to do a calculation efficiently? How should we look at a problem? Extensive effort is made to motivate the mathematics and isolate how one can apply ideas/perspectives to a variety of problems. As many of the key algorithms in the subject require too much time or detail to analyze in a first course (such as the run-time of the Simplex Algorithm), there are numerous comparisons to simpler algorithms which students have either seen or can quickly learn (such as the Euclidean algorithm) to motivate the type of results on run-time savings.