Analytical Methods Of Optimization

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Numerical Methods and Optimization

Author : Jean-Pierre Corriou
Publisher : Springer Nature
ISBN 13 : 3030893669
Total Pages : 730 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Numerical Methods and Optimization by : Jean-Pierre Corriou

Download or read book Numerical Methods and Optimization written by Jean-Pierre Corriou and published by Springer Nature. This book was released on 2022-01-04 with total page 730 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text, covering a very large span of numerical methods and optimization, is primarily aimed at advanced undergraduate and graduate students. A background in calculus and linear algebra are the only mathematical requirements. The abundance of advanced methods and practical applications will be attractive to scientists and researchers working in different branches of engineering. The reader is progressively introduced to general numerical methods and optimization algorithms in each chapter. Examples accompany the various methods and guide the students to a better understanding of the applications. The user is often provided with the opportunity to verify their results with complex programming code. Each chapter ends with graduated exercises which furnish the student with new cases to study as well as ideas for exam/homework problems for the instructor. A set of programs made in MatlabTM is available on the author’s personal website and presents both numerical and optimization methods.

Experimental Methods for the Analysis of Optimization Algorithms

Author : Thomas Bartz-Beielstein
Publisher : Springer Science & Business Media
ISBN 13 : 3642025382
Total Pages : 469 pages
Book Rating : 4.6/5 (42 download)

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Book Synopsis Experimental Methods for the Analysis of Optimization Algorithms by : Thomas Bartz-Beielstein

Download or read book Experimental Methods for the Analysis of Optimization Algorithms written by Thomas Bartz-Beielstein and published by Springer Science & Business Media. This book was released on 2010-11-02 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: In operations research and computer science it is common practice to evaluate the performance of optimization algorithms on the basis of computational results, and the experimental approach should follow accepted principles that guarantee the reliability and reproducibility of results. However, computational experiments differ from those in other sciences, and the last decade has seen considerable methodological research devoted to understanding the particular features of such experiments and assessing the related statistical methods. This book consists of methodological contributions on different scenarios of experimental analysis. The first part overviews the main issues in the experimental analysis of algorithms, and discusses the experimental cycle of algorithm development; the second part treats the characterization by means of statistical distributions of algorithm performance in terms of solution quality, runtime and other measures; and the third part collects advanced methods from experimental design for configuring and tuning algorithms on a specific class of instances with the goal of using the least amount of experimentation. The contributor list includes leading scientists in algorithm design, statistical design, optimization and heuristics, and most chapters provide theoretical background and are enriched with case studies. This book is written for researchers and practitioners in operations research and computer science who wish to improve the experimental assessment of optimization algorithms and, consequently, their design.

Analytical Methods of Optimization

Author : D. F. Lawden
Publisher : Courier Corporation
ISBN 13 : 0486450341
Total Pages : 178 pages
Book Rating : 4.4/5 (864 download)

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Book Synopsis Analytical Methods of Optimization by : D. F. Lawden

Download or read book Analytical Methods of Optimization written by D. F. Lawden and published by Courier Corporation. This book was released on 2006-05-05 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Suitable for advanced undergraduates and graduate students, this text surveys the classical theory of the calculus of variations. It takes the approach most appropriate for applications to problems of optimizing the behavior of engineering systems. Two of these problem areas have strongly influenced this presentation: the design of the control systems and the choice of rocket trajectories to be followed by terrestrial and extraterrestrial vehicles. Topics include static systems, control systems, additional constraints, the Hamilton-Jacobi equation, and the accessory optimization problem. Prerequisites include a course in the analysis of functions of many real variables and a familiarity with the elementary theory of ordinary differential equations, especially linear equations. Emphasis throughout the text is placed upon methods and principles, which are illustrated by worked problems and sets of exercises. Solutions to the exercises are available from the publisher upon request.

First-Order Methods in Optimization

Author : Amir Beck
Publisher : SIAM
ISBN 13 : 1611974984
Total Pages : 476 pages
Book Rating : 4.6/5 (119 download)

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Book Synopsis First-Order Methods in Optimization by : Amir Beck

Download or read book First-Order Methods in Optimization written by Amir Beck and published by SIAM. This book was released on 2017-10-02 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary goal of this book is to provide a self-contained, comprehensive study of the main ?rst-order methods that are frequently used in solving large-scale problems. First-order methods exploit information on values and gradients/subgradients (but not Hessians) of the functions composing the model under consideration. With the increase in the number of applications that can be modeled as large or even huge-scale optimization problems, there has been a revived interest in using simple methods that require low iteration cost as well as low memory storage. The author has gathered, reorganized, and synthesized (in a unified manner) many results that are currently scattered throughout the literature, many of which cannot be typically found in optimization books. First-Order Methods in Optimization offers comprehensive study of first-order methods with the theoretical foundations; provides plentiful examples and illustrations; emphasizes rates of convergence and complexity analysis of the main first-order methods used to solve large-scale problems; and covers both variables and functional decomposition methods.

Optimization for Data Analysis

Author : Stephen J. Wright
Publisher : Cambridge University Press
ISBN 13 : 1316518981
Total Pages : 239 pages
Book Rating : 4.3/5 (165 download)

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Book Synopsis Optimization for Data Analysis by : Stephen J. Wright

Download or read book Optimization for Data Analysis written by Stephen J. Wright and published by Cambridge University Press. This book was released on 2022-04-21 with total page 239 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise text that presents and analyzes the fundamental techniques and methods in optimization that are useful in data science.

Functional Analysis and Optimization Methods in Hadron Physics

Author : Irinel Caprini
Publisher : Springer
ISBN 13 : 3030189481
Total Pages : 139 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Functional Analysis and Optimization Methods in Hadron Physics by : Irinel Caprini

Download or read book Functional Analysis and Optimization Methods in Hadron Physics written by Irinel Caprini and published by Springer. This book was released on 2019-04-25 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book begins with a brief historical review of the early applications of standard dispersion relations in particle physics. It then presents the modern perspective within the Standard Model, emphasizing the relation of analyticity together with alternative tools applied to strong interactions, such as perturbative and lattice quantum chromodynamics (QCD), as well as chiral perturbation theory. The core of the book argues that, in order to improve the prediction of specific hadronic observables, it is often necessary to resort to methods of complex analysis more sophisticated than the simple Cauchy integral. Accordingly, a separate mathematical chapter is devoted to solving several functional analysis optimization problems. Their applications to physical amplitudes and form factors are discussed in the following chapters, which also demonstrate how to merge the analytic approach with statistical analysis tools. Given its scope, the book offers a valuable guide for researchers working in precision hadronic physics, as well as graduate students who are new to the field.

OPTIMIZATION METHODS FOR ENGINEERS

Author : N.V.S. Raju
Publisher : PHI Learning Pvt. Ltd.
ISBN 13 : 8120347447
Total Pages : 616 pages
Book Rating : 4.1/5 (23 download)

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Book Synopsis OPTIMIZATION METHODS FOR ENGINEERS by : N.V.S. Raju

Download or read book OPTIMIZATION METHODS FOR ENGINEERS written by N.V.S. Raju and published by PHI Learning Pvt. Ltd.. This book was released on 2014-01-01 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt: Primarily designed as a text for the postgraduate students of mechanical engineering and related branches, it provides an excellent introduction to optimization methods—the overview, the history, and the development. It is equally suitable for the undergraduate students for their electives. The text then moves on to familiarize the students with the formulation of optimization problems, graphical solutions, analytical methods of nonlinear optimization, classical optimization techniques, single variable (one-dimensional) unconstrained optimization, multidimensional problems, constrained optimization, equality and inequality constraints. With complexities of human life, the importance of optimization techniques as a tool has increased manifold. The application of optimization techniques creates an efficient, effective and a better life. Features • Includes numerous illustrations and unsolved problems. • Contains university questions. • Discusses the topics with step-by-step procedures.

Numerical Methods and Optimization

Author : Sergiy Butenko
Publisher : CRC Press
ISBN 13 : 1466577789
Total Pages : 408 pages
Book Rating : 4.4/5 (665 download)

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Book Synopsis Numerical Methods and Optimization by : Sergiy Butenko

Download or read book Numerical Methods and Optimization written by Sergiy Butenko and published by CRC Press. This book was released on 2014-03-11 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: For students in industrial and systems engineering (ISE) and operations research (OR) to understand optimization at an advanced level, they must first grasp the analysis of algorithms, computational complexity, and other concepts and modern developments in numerical methods. Satisfying this prerequisite, Numerical Methods and Optimization: An Intro

Analytical Methods for Dynamic Modelers

Author : Hazhir Rahmandad
Publisher : MIT Press
ISBN 13 : 0262331438
Total Pages : 443 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Analytical Methods for Dynamic Modelers by : Hazhir Rahmandad

Download or read book Analytical Methods for Dynamic Modelers written by Hazhir Rahmandad and published by MIT Press. This book was released on 2015-11-27 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: A user-friendly introduction to some of the most useful analytical tools for model building, estimation, and analysis, presenting key methods and examples. Simulation modeling is increasingly integrated into research and policy analysis of complex sociotechnical systems in a variety of domains. Model-based analysis and policy design inform a range of applications in fields from economics to engineering to health care. This book offers a hands-on introduction to key analytical methods for dynamic modeling. Bringing together tools and methodologies from fields as diverse as computational statistics, econometrics, and operations research in a single text, the book can be used for graduate-level courses and as a reference for dynamic modelers who want to expand their methodological toolbox. The focus is on quantitative techniques for use by dynamic modelers during model construction and analysis, and the material presented is accessible to readers with a background in college-level calculus and statistics. Each chapter describes a key method, presenting an introduction that emphasizes the basic intuition behind each method, tutorial style examples, references to key literature, and exercises. The chapter authors are all experts in the tools and methods they present. The book covers estimation of model parameters using quantitative data; understanding the links between model structure and its behavior; and decision support and optimization. An online appendix offers computer code for applications, models, and solutions to exercises. Contributors Wenyi An, Edward G. Anderson Jr., Yaman Barlas, Nishesh Chalise, Robert Eberlein, Hamed Ghoddusi, Winfried Grassmann, Peter S. Hovmand, Mohammad S. Jalali, Nitin Joglekar, David Keith, Juxin Liu, Erling Moxnes, Rogelio Oliva, Nathaniel D. Osgood, Hazhir Rahmandad, Raymond Spiteri, John Sterman, Jeroen Struben, Burcu Tan, Karen Yee, Gönenç Yücel

Advances in Optimization and Numerical Analysis

Author : S. Gomez
Publisher : Springer Science & Business Media
ISBN 13 : 9401583307
Total Pages : 285 pages
Book Rating : 4.4/5 (15 download)

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Book Synopsis Advances in Optimization and Numerical Analysis by : S. Gomez

Download or read book Advances in Optimization and Numerical Analysis written by S. Gomez and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: In January 1992, the Sixth Workshop on Optimization and Numerical Analysis was held in the heart of the Mixteco-Zapoteca region, in the city of Oaxaca, Mexico, a beautiful and culturally rich site in ancient, colonial and modern Mexican civiliza tion. The Workshop was organized by the Numerical Analysis Department at the Institute of Research in Applied Mathematics of the National University of Mexico in collaboration with the Mathematical Sciences Department at Rice University, as were the previous ones in 1978, 1979, 1981, 1984 and 1989. As were the third, fourth, and fifth workshops, this one was supported by a grant from the Mexican National Council for Science and Technology, and the US National Science Foundation, as part of the joint Scientific and Technical Cooperation Program existing between these two countries. The participation of many of the leading figures in the field resulted in a good representation of the state of the art in Continuous Optimization, and in an over view of several topics including Numerical Methods for Diffusion-Advection PDE problems as well as some Numerical Linear Algebraic Methods to solve related pro blems. This book collects some of the papers given at this Workshop.

Newton-Type Methods for Optimization and Variational Problems

Author : Alexey F. Izmailov
Publisher : Springer
ISBN 13 : 3319042475
Total Pages : 587 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Newton-Type Methods for Optimization and Variational Problems by : Alexey F. Izmailov

Download or read book Newton-Type Methods for Optimization and Variational Problems written by Alexey F. Izmailov and published by Springer. This book was released on 2014-07-08 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents comprehensive state-of-the-art theoretical analysis of the fundamental Newtonian and Newtonian-related approaches to solving optimization and variational problems. A central focus is the relationship between the basic Newton scheme for a given problem and algorithms that also enjoy fast local convergence. The authors develop general perturbed Newtonian frameworks that preserve fast convergence and consider specific algorithms as particular cases within those frameworks, i.e., as perturbations of the associated basic Newton iterations. This approach yields a set of tools for the unified treatment of various algorithms, including some not of the Newton type per se. Among the new subjects addressed is the class of degenerate problems. In particular, the phenomenon of attraction of Newton iterates to critical Lagrange multipliers and its consequences as well as stabilized Newton methods for variational problems and stabilized sequential quadratic programming for optimization. This volume will be useful to researchers and graduate students in the fields of optimization and variational analysis.

Convex Analysis and Global Optimization

Author : Hoang Tuy
Publisher : Springer Science & Business Media
ISBN 13 : 1475728093
Total Pages : 346 pages
Book Rating : 4.4/5 (757 download)

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Book Synopsis Convex Analysis and Global Optimization by : Hoang Tuy

Download or read book Convex Analysis and Global Optimization written by Hoang Tuy and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the general complementary convex structure underlying most nonconvex optimization problems encountered in applications, convex analysis plays an essential role in the development of global optimization methods. This book develops a coherent and rigorous theory of deterministic global optimization from this point of view. Part I constitutes an introduction to convex analysis, with an emphasis on concepts, properties and results particularly needed for global optimization, including those pertaining to the complementary convex structure. Part II presents the foundation and application of global search principles such as partitioning and cutting, outer and inner approximation, and decomposition to general global optimization problems and to problems with a low-rank nonconvex structure as well as quadratic problems. Much new material is offered, aside from a rigorous mathematical development. Audience: The book is written as a text for graduate students in engineering, mathematics, operations research, computer science and other disciplines dealing with optimization theory. It is also addressed to all scientists in various fields who are interested in mathematical optimization.

Convex Optimization Algorithms

Author : Dimitri Bertsekas
Publisher : Athena Scientific
ISBN 13 : 1886529280
Total Pages : 576 pages
Book Rating : 4.8/5 (865 download)

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Book Synopsis Convex Optimization Algorithms by : Dimitri Bertsekas

Download or read book Convex Optimization Algorithms written by Dimitri Bertsekas and published by Athena Scientific. This book was released on 2015-02-01 with total page 576 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and accessible presentation of algorithms for solving convex optimization problems. It relies on rigorous mathematical analysis, but also aims at an intuitive exposition that makes use of visualization where possible. This is facilitated by the extensive use of analytical and algorithmic concepts of duality, which by nature lend themselves to geometrical interpretation. The book places particular emphasis on modern developments, and their widespread applications in fields such as large-scale resource allocation problems, signal processing, and machine learning. The book is aimed at students, researchers, and practitioners, roughly at the first year graduate level. It is similar in style to the author's 2009"Convex Optimization Theory" book, but can be read independently. The latter book focuses on convexity theory and optimization duality, while the present book focuses on algorithmic issues. The two books share notation, and together cover the entire finite-dimensional convex optimization methodology. To facilitate readability, the statements of definitions and results of the "theory book" are reproduced without proofs in Appendix B.

Nonlinear Analysis and Global Optimization

Author : Themistocles M. Rassias
Publisher : Springer Nature
ISBN 13 : 3030617327
Total Pages : 484 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Nonlinear Analysis and Global Optimization by : Themistocles M. Rassias

Download or read book Nonlinear Analysis and Global Optimization written by Themistocles M. Rassias and published by Springer Nature. This book was released on 2021-02-26 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume discusses aspects of nonlinear analysis in which optimization plays an important role, as well as topics which are applied to the study of optimization problems. Topics include set-valued analysis, mixed concave-convex sub-superlinear Schroedinger equation, Schroedinger equations in nonlinear optics, exponentially convex functions, optimal lot size under the occurrence of imperfect quality items, generalized equilibrium problems, artificial topologies on a relativistic spacetime, equilibrium points in the restricted three-body problem, optimization models for networks of organ transplants, network curvature measures, error analysis through energy minimization and stability problems, Ekeland variational principles in 2-local Branciari metric spaces, frictional dynamic problems, norm estimates for composite operators, operator factorization and solution of second-order nonlinear difference equations, degenerate Kirchhoff-type inclusion problems, and more.

Numerical Methods and Optimization in Finance

Author : Manfred Gilli
Publisher : Academic Press
ISBN 13 : 0128150653
Total Pages : 638 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Numerical Methods and Optimization in Finance by : Manfred Gilli

Download or read book Numerical Methods and Optimization in Finance written by Manfred Gilli and published by Academic Press. This book was released on 2019-08-16 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computationally-intensive tools play an increasingly important role in financial decisions. Many financial problems-ranging from asset allocation to risk management and from option pricing to model calibration-can be efficiently handled using modern computational techniques. Numerical Methods and Optimization in Finance presents such computational techniques, with an emphasis on simulation and optimization, particularly so-called heuristics. This book treats quantitative analysis as an essentially computational discipline in which applications are put into software form and tested empirically. This revised edition includes two new chapters, a self-contained tutorial on implementing and using heuristics, and an explanation of software used for testing portfolio-selection models. Postgraduate students, researchers in programs on quantitative and computational finance, and practitioners in banks and other financial companies can benefit from this second edition of Numerical Methods and Optimization in Finance.

Iterative Methods for Optimization

Author : C. T. Kelley
Publisher : SIAM
ISBN 13 : 9781611970920
Total Pages : 195 pages
Book Rating : 4.9/5 (79 download)

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Book Synopsis Iterative Methods for Optimization by : C. T. Kelley

Download or read book Iterative Methods for Optimization written by C. T. Kelley and published by SIAM. This book was released on 1999-01-01 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a carefully selected group of methods for unconstrained and bound constrained optimization problems and analyzes them in depth both theoretically and algorithmically. It focuses on clarity in algorithmic description and analysis rather than generality, and while it provides pointers to the literature for the most general theoretical results and robust software, the author thinks it is more important that readers have a complete understanding of special cases that convey essential ideas. A companion to Kelley's book, Iterative Methods for Linear and Nonlinear Equations (SIAM, 1995), this book contains many exercises and examples and can be used as a text, a tutorial for self-study, or a reference. Iterative Methods for Optimization does more than cover traditional gradient-based optimization: it is the first book to treat sampling methods, including the Hooke-Jeeves, implicit filtering, MDS, and Nelder-Mead schemes in a unified way, and also the first book to make connections between sampling methods and the traditional gradient-methods. Each of the main algorithms in the text is described in pseudocode, and a collection of MATLAB codes is available. Thus, readers can experiment with the algorithms in an easy way as well as implement them in other languages.

Introduction to Optimization Methods and their Application in Statistics

Author : B. Everitt
Publisher : Springer Science & Business Media
ISBN 13 : 9400931530
Total Pages : 87 pages
Book Rating : 4.4/5 (9 download)

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Book Synopsis Introduction to Optimization Methods and their Application in Statistics by : B. Everitt

Download or read book Introduction to Optimization Methods and their Application in Statistics written by B. Everitt and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 87 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimization techniques are used to find the values of a set of parameters which maximize or minimize some objective function of interest. Such methods have become of great importance in statistics for estimation, model fitting, etc. This text attempts to give a brief introduction to optimization methods and their use in several important areas of statistics. It does not pretend to provide either a complete treatment of optimization techniques or a comprehensive review of their application in statistics; such a review would, of course, require a volume several orders of magnitude larger than this since almost every issue of every statistics journal contains one or other paper which involves the application of an optimization method. It is hoped that the text will be useful to students on applied statistics courses and to researchers needing to use optimization techniques in a statistical context. Lastly, my thanks are due to Bertha Lakey for typing the manuscript.