introduction to applied optimization

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Introduction To Applied Optimization

Author : Urmila Diwekar
ISBN : 9781475737455
Genre : Mathematics
File Size : 58. 6 MB
Format : PDF
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This text presents a multi-disciplined view of optimization, providing students and researchers with a thorough examination of algorithms, methods, and tools from diverse areas of optimization without introducing excessive theoretical detail. This second edition includes additional topics, including global optimization and a real-world case study using important concepts from each chapter. Introduction to Applied Optimization is intended for advanced undergraduate and graduate students and will benefit scientists from diverse areas, including engineers.

Introduction To Applied Optimization

Author : Urmila Diwekar
ISBN : 9780387766355
Genre : Mathematics
File Size : 30. 27 MB
Format : PDF
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Provides well-written self-contained chapters, including problem sets and exercises, making it ideal for the classroom setting; Introduces applied optimization to the hazardous waste blending problem; Explores linear programming, nonlinear programming, discrete optimization, global optimization, optimization under uncertainty, multi-objective optimization, optimal control and stochastic optimal control; Includes an extensive bibliography at the end of each chapter and an index; GAMS files of case studies for Chapters 2, 3, 4, 5, and 7 are linked to http://www.springer.com/math/book/978-0-387-76634-8; Solutions manual available upon adoptions.

Introduction To Applied Optimization

Author : Urmila Diwekar
ISBN : 1402074565
Genre : Mathematics
File Size : 64. 38 MB
Format : PDF, ePub
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This text presents a multi-disciplined view of optimization, providing students and researchers with a thorough examination of algorithms, methods, and tools from diverse areas of optimization without introducing excessive theoretical detail. This second edition includes additional topics, including global optimization and a real-world case study using important concepts from each chapter. Introduction to Applied Optimization is intended for advanced undergraduate and graduate students and will benefit scientists from diverse areas, including engineers.

Applied Optimization With Matlab Programming

Author : P. Venkataraman
ISBN : 9780470084885
Genre : Technology & Engineering
File Size : 34. 14 MB
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Over the last few decades, optimization techniques have been streamlined by the use of computers and artificial intelligence methods to analyze more variables (especially under non-linear, multivariable conditions) more quickly than ever before. This book covers all classical linear and nonlinear optimization techniques while focusing on the standard mathematical engine, MATLAB. As with the first edition, the author uses MATLAB in examples for running computer-based optimization problems. New coverage in this edition includes design optimization techniques such as Multidisciplinary Optimization, Explicit Solution for Boundary Value Problems, and Particle Swarm Optimization.

Introduction To Optimization

Author : Pablo Pedregal
ISBN : 9780387216805
Genre : Mathematics
File Size : 82. 66 MB
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This undergraduate textbook introduces students of science and engineering to the fascinating field of optimization. It is a unique book that brings together the subfields of mathematical programming, variational calculus, and optimal control, thus giving students an overall view of all aspects of optimization in a single reference. As a primer on optimization, its main goal is to provide a succinct and accessible introduction to linear programming, nonlinear programming, numerical optimization algorithms, variational problems, dynamic programming, and optimal control. Prerequisites have been kept to a minimum, although a basic knowledge of calculus, linear algebra, and differential equations is assumed.

Applied Optimization

Author : Ross Baldick
ISBN : 9781107394087
Genre : Technology & Engineering
File Size : 54. 36 MB
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The starting point in the formulation of any numerical problem is to take an intuitive idea about the problem in question and to translate it into precise mathematical language. This book provides step-by-step descriptions of how to formulate numerical problems and develops techniques for solving them. A number of engineering case studies motivate the development of efficient algorithms that involve, in some cases, transformation of the problem from its initial formulation into a more tractable form. Five general problem classes are considered: linear systems of equations, non-linear systems of equations, unconstrained optimization, equality-constrained optimization and inequality-constrained optimization. The book contains many worked examples and homework exercises and is suitable for students of engineering or operations research taking courses in optimization. Supplementary material including solutions, lecture slides and appendices are available online at www.cambridge.org/9780521855648.

Practical Mathematical Optimization

Author : Jan Snyman
ISBN : 0387243488
Genre : Business & Economics
File Size : 28. 75 MB
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It is intended that this book be used in senior- to graduate-level semester courses in optimization, as offered in mathematics, engineering, com puter science and operations research departments. Hopefully this book will also be useful to practising professionals in the workplace. The contents of the book represent the fundamental optimization mate rial collected and used by the author, over a period of more than twenty years, in teaching Practical Mathematical Optimization to undergradu ate as well as graduate engineering and science students at the University of Pretoria. The principal motivation for writing this work has not been the teaching of mathematics per se, but to equip students with the nec essary fundamental optimization theory and algorithms, so as to enable them to solve practical problems in their own particular principal fields of interest, be it physics, chemistry, engineering design or business eco nomics. The particular approach adopted here follows from the author's own personal experiences in doing research in solid-state physics and in mechanical engineering design, where he was constantly confronted by problems that can most easily and directly be solved via the judicious use of mathematical optimization techniques. This book is, however, not a collection of case studies restricted to the above-mentioned specialized research areas, but is intended to convey the basic optimization princi ples and algorithms to a general audience in such a way that, hopefully, the application to their own practical areas of interest will be relatively simple and straightforward.

Mathematical Programming

Author : Melvyn Jeter
ISBN : 0824774787
Genre : Business & Economics
File Size : 62. 91 MB
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Introduction To Nonlinear And Global Optimization

Author : Eligius M.T. Hendrix
ISBN : 9780387886701
Genre : Mathematics
File Size : 55. 3 MB
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This self-contained text provides a solid introduction to global and nonlinear optimization, providing students of mathematics and interdisciplinary sciences with a strong foundation in applied optimization techniques. The book offers a unique hands-on and critical approach to applied optimization which includes the presentation of numerous algorithms, examples, and illustrations, designed to improve the reader’s intuition and develop the analytical skills needed to identify optimization problems, classify the structure of a model, and determine whether a solution fulfills optimality conditions.

Introduction To Nonlinear Optimization

Author : Amir Beck
ISBN : 9781611973648
Genre : Mathematics
File Size : 79. 52 MB
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This book provides the foundations of the theory of nonlinear optimization as well as some related algorithms and presents a variety of applications from diverse areas of applied sciences. The author combines three pillars of optimization?theoretical and algorithmic foundation, familiarity with various applications, and the ability to apply the theory and algorithms on actual problems?and rigorously and gradually builds the connection between theory, algorithms, applications, and implementation. Readers will find more than 170 theoretical, algorithmic, and numerical exercises that deepen and enhance the reader's understanding of the topics. The author includes offers several subjects not typically found in optimization books?for example, optimality conditions in sparsity-constrained optimization, hidden convexity, and total least squares. The book also offers a large number of applications discussed theoretically and algorithmically, such as circle fitting, Chebyshev center, the Fermat?Weber problem, denoising, clustering, total least squares, and orthogonal regression and theoretical and algorithmic topics demonstrated by the MATLAB? toolbox CVX and a package of m-files that is posted on the book?s web site.

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