Practical Optimization with MATLAB

Practical Optimization with MATLAB
Author: Mircea Ancău
Publisher: Cambridge Scholars Publishing
Total Pages: 291
Release: 2019-10-03
Genre: Mathematics
ISBN: 1527540987
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This easy-to-follow guide provides academics and industrial engineers with a state-of-the-art numerical approach to the most frequent technical and economical optimization methods. In an engaging manner, it provides the reader with not only a systematic and comprehensive study, but also with necessary and directly implementable code written in the versatile and readily available platform Matlab. The book offers optimization methods for univariate and multivariate constrained or unconstrained functions, general optimization methods and multicriteria optimization methods; provides intuitively, step-by-step explained sample Matlab code, that can be easily adjusted to meet individual requirements; and uses a clear, concise presentation style, which will be suited to readers even without a programming background, as well as to students preparing for examinations in optimization methods.

Optimization in Practice with MATLAB

Optimization in Practice with MATLAB
Author: Achille Messac
Publisher: Cambridge University Press
Total Pages: 503
Release: 2015-03-19
Genre: Computers
ISBN: 1107109183
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This textbook is designed for students and industry practitioners for a first course in optimization integrating MATLAB® software.

Practical Optimization

Practical Optimization
Author: Philip E. Gill
Publisher: SIAM
Total Pages: 421
Release: 2019-12-16
Genre: Mathematics
ISBN: 1611975603
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In the intervening years since this book was published in 1981, the field of optimization has been exceptionally lively. This fertility has involved not only progress in theory, but also faster numerical algorithms and extensions into unexpected or previously unknown areas such as semidefinite programming. Despite these changes, many of the important principles and much of the intuition can be found in this Classics version of Practical Optimization. This book provides model algorithms and pseudocode, useful tools for users who prefer to write their own code as well as for those who want to understand externally provided code. It presents algorithms in a step-by-step format, revealing the overall structure of the underlying procedures and thereby allowing a high-level perspective on the fundamental differences. And it contains a wealth of techniques and strategies that are well suited for optimization in the twenty-first century, and particularly in the now-flourishing fields of data science, “big data,” and machine learning. Practical Optimization is appropriate for advanced undergraduates, graduate students, and researchers interested in methods for solving optimization problems.

Applied Optimization with MATLAB Programming

Applied Optimization with MATLAB Programming
Author: P. Venkataraman
Publisher: John Wiley & Sons
Total Pages: 546
Release: 2009-03-23
Genre: Technology & Engineering
ISBN: 047008488X
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Technology/Engineering/Mechanical Provides all the tools needed to begin solving optimization problems using MATLAB® The Second Edition of Applied Optimization with MATLAB® Programming enables readers to harness all the features of MATLAB® to solve optimization problems using a variety of linear and nonlinear design optimization techniques. By breaking down complex mathematical concepts into simple ideas and offering plenty of easy-to-follow examples, this text is an ideal introduction to the field. Examples come from all engineering disciplines as well as science, economics, operations research, and mathematics, helping readers understand how to apply optimization techniques to solve actual problems. This Second Edition has been thoroughly revised, incorporating current optimization techniques as well as the improved MATLAB® tools. Two important new features of the text are: Introduction to the scan and zoom method, providing a simple, effective technique that works for unconstrained, constrained, and global optimization problems New chapter, Hybrid Mathematics: An Application, using examples to illustrate how optimization can develop analytical or explicit solutions to differential systems and data-fitting problems Each chapter ends with a set of problems that give readers an opportunity to put their new skills into practice. Almost all of the numerical techniques covered in the text are supported by MATLAB® code, which readers can download on the text's companion Web site www.wiley.com/go/venkat2e and use to begin solving problems on their own. This text is recommended for upper-level undergraduate and graduate students in all areas of engineering as well as other disciplines that use optimization techniques to solve design problems.

Practical Optimization

Practical Optimization
Author: Andreas Antoniou
Publisher: Springer Science & Business Media
Total Pages: 675
Release: 2007-03-12
Genre: Computers
ISBN: 0387711066
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Practical Optimization: Algorithms and Engineering Applications is a hands-on treatment of the subject of optimization. A comprehensive set of problems and exercises makes the book suitable for use in one or two semesters of a first-year graduate course or an advanced undergraduate course. Each half of the book contains a full semester’s worth of complementary yet stand-alone material. The practical orientation of the topics chosen and a wealth of useful examples also make the book suitable for practitioners in the field.

MATLAB Optimization Techniques

MATLAB Optimization Techniques
Author: Cesar Lopez
Publisher: Apress
Total Pages: 284
Release: 2014-11-12
Genre: Computers
ISBN: 1484202929
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MATLAB is a high-level language and environment for numerical computation, visualization, and programming. Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java. MATLAB Optimization Techniques introduces you to the MATLAB language with practical hands-on instructions and results, allowing you to quickly achieve your goals. It begins by introducing the MATLAB environment and the structure of MATLAB programming before moving on to the mathematics of optimization. The central part of the book is dedicated to MATLAB’s Optimization Toolbox, which implements state-of-the-art algorithms for solving multiobjective problems, non-linear minimization with boundary conditions and restrictions, minimax optimization, semi-infinitely constrained minimization and linear and quadratic programming. A wide range of exercises and examples are included, illustrating the most widely used optimization methods.

A Practical Approach to Metaheuristics Using LabVIEW and MATLAB®

A Practical Approach to Metaheuristics Using LabVIEW and MATLAB®
Author: Arturo Molina Gutiérrez
Publisher: Chapman & Hall/CRC
Total Pages: 158
Release: 2020
Genre: Computer graphics
ISBN: 9780367494261
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This book describes and implements metaheuristic algorithms, using a practical approach in which engineering problems are solved. A novel optimization algorithm, called Earthquake optimization, is presented as a main example. Since this algorithm is used for earthquake modeling, a geological optimization strategy is demonstrated.

Introduction to Nature-Inspired Optimization

Introduction to Nature-Inspired Optimization
Author: George Lindfield
Publisher: Academic Press
Total Pages: 258
Release: 2017-08-10
Genre: Mathematics
ISBN: 0128036664
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Introduction to Nature-Inspired Optimization brings together many of the innovative mathematical methods for non-linear optimization that have their origins in the way various species behave in order to optimize their chances of survival. The book describes each method, examines their strengths and weaknesses, and where appropriate, provides the MATLAB code to give practical insight into the detailed structure of these methods and how they work. Nature-inspired algorithms emulate processes that are found in the natural world, spurring interest for optimization. Lindfield/Penny provide concise coverage to all the major algorithms, including genetic algorithms, artificial bee colony algorithms, ant colony optimization and the cuckoo search algorithm, among others. This book provides a quick reference to practicing engineers, researchers and graduate students who work in the field of optimization. Applies concepts in nature and biology to develop new algorithms for nonlinear optimization Offers working MATLAB® programs for the major algorithms described, applying them to a range of problems Provides useful comparative studies of the algorithms, highlighting their strengths and weaknesses Discusses the current state-of-the-field and indicates possible areas of future development

Applied Dynamic Programming for Optimization of Dynamical Systems

Applied Dynamic Programming for Optimization of Dynamical Systems
Author: Rush D. Robinett III
Publisher: SIAM
Total Pages: 278
Release: 2005-01-01
Genre: Mathematics
ISBN: 9780898718676
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Based on the results of over 10 years of research and development by the authors, this book presents a broad cross section of dynamic programming (DP) techniques applied to the optimization of dynamical systems. The main goal of the research effort was to develop a robust path planning/trajectory optimization tool that did not require an initial guess. The goal was partially met with a combination of DP and homotopy algorithms. DP algorithms are presented here with a theoretical development, and their successful application to variety of practical engineering problems is emphasized.

Practical Numerical and Scientific Computing with MATLAB® and Python

Practical Numerical and Scientific Computing with MATLAB® and Python
Author: Eihab B. M. Bashier
Publisher: CRC Press
Total Pages: 349
Release: 2020-03-18
Genre: Computers
ISBN: 0429666829
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Practical Numerical and Scientific Computing with MATLAB® and Python concentrates on the practical aspects of numerical analysis and linear and non-linear programming. It discusses the methods for solving different types of mathematical problems using MATLAB and Python. Although the book focuses on the approximation problem rather than on error analysis of mathematical problems, it provides practical ways to calculate errors. The book is divided into three parts, covering topics in numerical linear algebra, methods of interpolation, numerical differentiation and integration, solutions of differential equations, linear and non-linear programming problems, and optimal control problems. This book has the following advantages: It adopts the programming languages, MATLAB and Python, which are widely used among academics, scientists, and engineers, for ease of use and contain many libraries covering many scientific and engineering fields. It contains topics that are rarely found in other numerical analysis books, such as ill-conditioned linear systems and methods of regularization to stabilize their solutions, nonstandard finite differences methods for solutions of ordinary differential equations, and the computations of the optimal controls. It provides a practical explanation of how to apply these topics using MATLAB and Python. It discusses software libraries to solve mathematical problems, such as software Gekko, pulp, and pyomo. These libraries use Python for solutions to differential equations and static and dynamic optimization problems. Most programs in the book can be applied in versions prior to MATLAB 2017b and Python 3.7.4 without the need to modify these programs. This book is aimed at newcomers and middle-level students, as well as members of the scientific community who are interested in solving math problems using MATLAB or Python.