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Introduction to Optimization Methods

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Release : 2013-03-09
Genre : Science
Kind : eBook
Book Rating : 05X/5 ( reviews)

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Book Synopsis Introduction to Optimization Methods by : P. Adby

Download or read book Introduction to Optimization Methods written by P. Adby. This book was released on 2013-03-09. Available in PDF, EPUB and Kindle. Book excerpt: During the last decade the techniques of non-linear optim ization have emerged as an important subject for study and research. The increasingly widespread application of optim ization has been stimulated by the availability of digital computers, and the necessity of using them in the investigation of large systems. This book is an introduction to non-linear methods of optimization and is suitable for undergraduate and post graduate courses in mathematics, the physical and social sciences, and engineering. The first half of the book covers the basic optimization techniques including linear search methods, steepest descent, least squares, and the Newton-Raphson method. These are described in detail, with worked numerical examples, since they form the basis from which advanced methods are derived. Since 1965 advanced methods of unconstrained and constrained optimization have been developed to utilise the computational power of the digital computer. The second half of the book describes fully important algorithms in current use such as variable metric methods for unconstrained problems and penalty function methods for constrained problems. Recent work, much of which has not yet been widely applied, is reviewed and compared with currently popular techniques under a few generic main headings. vi PREFACE Chapter I describes the optimization problem in mathemat ical form and defines the terminology used in the remainder of the book. Chapter 2 is concerned with single variable optimization. The main algorithms of both search and approximation methods are developed in detail since they are an essential part of many multi-variable methods.

An Introduction to Optimization

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Release : 2004-04-05
Genre : Mathematics
Kind : eBook
Book Rating : 000/5 ( reviews)

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Book Synopsis An Introduction to Optimization by : Edwin K. P. Chong

Download or read book An Introduction to Optimization written by Edwin K. P. Chong. This book was released on 2004-04-05. Available in PDF, EPUB and Kindle. Book excerpt: A modern, up-to-date introduction to optimization theory and methods This authoritative book serves as an introductory text to optimization at the senior undergraduate and beginning graduate levels. With consistently accessible and elementary treatment of all topics, An Introduction to Optimization, Second Edition helps students build a solid working knowledge of the field, including unconstrained optimization, linear programming, and constrained optimization. Supplemented with more than one hundred tables and illustrations, an extensive bibliography, and numerous worked examples to illustrate both theory and algorithms, this book also provides: * A review of the required mathematical background material * A mathematical discussion at a level accessible to MBA and business students * A treatment of both linear and nonlinear programming * An introduction to recent developments, including neural networks, genetic algorithms, and interior-point methods * A chapter on the use of descent algorithms for the training of feedforward neural networks * Exercise problems after every chapter, many new to this edition * MATLAB(r) exercises and examples * Accompanying Instructor's Solutions Manual available on request An Introduction to Optimization, Second Edition helps students prepare for the advanced topics and technological developments that lie ahead. It is also a useful book for researchers and professionals in mathematics, electrical engineering, economics, statistics, and business. An Instructor's Manual presenting detailed solutions to all the problems in the book is available from the Wiley editorial department.

Introduction to Optimization Methods and their Application in Statistics

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Release : 2012-12-06
Genre : Science
Kind : eBook
Book Rating : 530/5 ( reviews)

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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. This book was released on 2012-12-06. 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.

An Introduction to Optimization Techniques

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Release : 2021-04-19
Genre : Mathematics
Kind : eBook
Book Rating : 231/5 ( reviews)

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Book Synopsis An Introduction to Optimization Techniques by : Vikrant Sharma

Download or read book An Introduction to Optimization Techniques written by Vikrant Sharma. This book was released on 2021-04-19. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Optimization Techniques introduces the basic ideas and techniques of optimization. Optimization is a precise procedure using design constraints and criteria to enable the planner to find the optimal solution. Optimization techniques have been applied in numerous fields to deal with different practical problems. This book is designed to give the reader a sense of the challenge of analyzing a given situation and formulating a model for it while explaining the assumptions and inner structure of the methods discussed as fully as possible. It includes real-world examples and applications making the book accessible to a broader readership. Features Each chapter begins with the Learning Outcomes (LO) section, which highlights the critical points of that chapter. All learning outcomes, solved examples and questions are mapped to six Bloom Taxonomy levels (BT Level). Book offers fundamental concepts of optimization without becoming too complicated. A wide range of solved examples are presented in each section after the theoretical discussion to clarify the concept of that section. A separate chapter on the application of spreadsheets to solve different optimization techniques. At the end of each chapter, a summary reinforces key ideas and helps readers recall the concepts discussed. The wide and emerging uses of optimization techniques make it essential for students and professionals. Optimization techniques have been applied in numerous fields to deal with different practical problems. This book serves as a textbook for UG and PG students of science, engineering, and management programs. It will be equally useful for Professionals, Consultants, and Managers.

Fundamentals of Optimization Techniques with Algorithms

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Release : 2020-08-25
Genre : Technology & Engineering
Kind : eBook
Book Rating : 924/5 ( reviews)

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Book Synopsis Fundamentals of Optimization Techniques with Algorithms by : Sukanta Nayak

Download or read book Fundamentals of Optimization Techniques with Algorithms written by Sukanta Nayak. This book was released on 2020-08-25. Available in PDF, EPUB and Kindle. Book excerpt: Optimization is a key concept in mathematics, computer science, and operations research, and is essential to the modeling of any system, playing an integral role in computer-aided design. Fundamentals of Optimization Techniques with Algorithms presents a complete package of various traditional and advanced optimization techniques along with a variety of example problems, algorithms and MATLAB© code optimization techniques, for linear and nonlinear single variable and multivariable models, as well as multi-objective and advanced optimization techniques. It presents both theoretical and numerical perspectives in a clear and approachable way. In order to help the reader apply optimization techniques in practice, the book details program codes and computer-aided designs in relation to real-world problems. Ten chapters cover, an introduction to optimization; linear programming; single variable nonlinear optimization; multivariable unconstrained nonlinear optimization; multivariable constrained nonlinear optimization; geometric programming; dynamic programming; integer programming; multi-objective optimization; and nature-inspired optimization. This book provides accessible coverage of optimization techniques, and helps the reader to apply them in practice. Presents optimization techniques clearly, including worked-out examples, from traditional to advanced Maps out the relations between optimization and other mathematical topics and disciplines Provides systematic coverage of algorithms to facilitate computer coding Gives MATLAB© codes in relation to optimization techniques and their use in computer-aided design Presents nature-inspired optimization techniques including genetic algorithms and artificial neural networks

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