Introduction to Linear Programming with MATLAB

Introduction to Linear Programming with MATLAB
Author: Shashi Kant Mishra
Publisher: CRC Press
Total Pages: 313
Release: 2017-09-07
Genre: Mathematics
ISBN: 1351596802

This book is based on the lecture notes of the author delivered to the students at the Institute of Science, Banaras Hindu University, India. It covers simplex, revised simplex, two-phase method, duality, dual simplex, complementary slackness, transportation and assignment problems with good number of examples, clear proofs, MATLAB codes and homework problems. The book will be useful for both students and practitioners.

Linear Programming with MATLAB

Linear Programming with MATLAB
Author: Michael C. Ferris
Publisher: SIAM
Total Pages: 270
Release: 2007-01-01
Genre: Mathematics
ISBN: 0898716438

A self-contained introduction to linear programming using MATLAB® software to elucidate the development of algorithms and theory. Exercises are included in each chapter, and additional information is provided in two appendices and an accompanying Web site. Only a basic knowledge of linear algebra and calculus is required.

Linear Programming Using MATLAB®

Linear Programming Using MATLAB®
Author: Nikolaos Ploskas
Publisher: Springer
Total Pages: 646
Release: 2017-10-28
Genre: Mathematics
ISBN: 3319659197

This book offers a theoretical and computational presentation of a variety of linear programming algorithms and methods with an emphasis on the revised simplex method and its components. A theoretical background and mathematical formulation is included for each algorithm as well as comprehensive numerical examples and corresponding MATLAB® code. The MATLAB® implementations presented in this book are sophisticated and allow users to find solutions to large-scale benchmark linear programs. Each algorithm is followed by a computational study on benchmark problems that analyze the computational behavior of the presented algorithms. As a solid companion to existing algorithmic-specific literature, this book will be useful to researchers, scientists, mathematical programmers, and students with a basic knowledge of linear algebra and calculus. The clear presentation enables the reader to understand and utilize all components of simplex-type methods, such as presolve techniques, scaling techniques, pivoting rules, basis update methods, and sensitivity analysis.

Introduction to Linear Optimization and Extensions with MATLAB

Introduction to Linear Optimization and Extensions with MATLAB
Author: Roy H. Kwon
Publisher: CRC Press
Total Pages: 356
Release: 2013-09-05
Genre: Business & Economics
ISBN: 1482204347

Filling the need for an introductory book on linear programming that discusses the important ways to mitigate parameter uncertainty, Introduction to Linear Optimization and Extensions with MATLAB provides a concrete and intuitive yet rigorous introduction to modern linear optimization. In addition to fundamental topics, the book discusses current l

Nonlinear Optimization in Electrical Engineering with Applications in MATLAB®

Nonlinear Optimization in Electrical Engineering with Applications in MATLAB®
Author: Mohamed Bakr
Publisher: IET
Total Pages: 325
Release: 2013-09-09
Genre: Computers
ISBN: 1849195439

Nonlinear Optimization in Electrical Engineering with Applications in MATLAB® provides an introductory course on nonlinear optimization in electrical engineering, with a focus on applications such as the design of electric, microwave, and photonic circuits, wireless communications, and digital filter design.

An Introduction to MATLAB® Programming and Numerical Methods for Engineers

An Introduction to MATLAB® Programming and Numerical Methods for Engineers
Author: Timmy Siauw
Publisher: Academic Press
Total Pages: 339
Release: 2014-04-05
Genre: Computers
ISBN: 0127999140

Assuming no prior background in linear algebra or real analysis, An Introduction to MATLAB® Programming and Numerical Methods for Engineers enables you to develop good computational problem solving techniques through the use of numerical methods and the MATLAB® programming environment. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level allowing you to quickly apply results in practical settings. - Tips, warnings, and "try this" features within each chapter help the reader develop good programming practices - Chapter summaries, key terms, and functions and operators lists at the end of each chapter allow for quick access to important information - At least three different types of end of chapter exercises — thinking, writing, and coding — let you assess your understanding and practice what you've learned

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

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.

An Introduction to Programming and Numerical Methods in MATLAB

An Introduction to Programming and Numerical Methods in MATLAB
Author: Steve Otto
Publisher: Springer Science & Business Media
Total Pages: 469
Release: 2005-12-06
Genre: Mathematics
ISBN: 1846281334

An elementary first course for students in mathematics and engineering Practical in approach: examples of code are provided for students to debug, and tasks – with full solutions – are provided at the end of each chapter Includes a glossary of useful terms, with each term supported by an example of the syntaxes commonly encountered

An Introduction to Optimization

An Introduction to Optimization
Author: Edwin K. P. Chong
Publisher: John Wiley & Sons
Total Pages: 646
Release: 2013-02-05
Genre: Mathematics
ISBN: 1118515153

Praise for the Third Edition ". . . guides and leads the reader through the learning path . . . [e]xamples are stated very clearly and the results are presented with attention to detail." —MAA Reviews Fully updated to reflect new developments in the field, the Fourth Edition of Introduction to Optimization fills the need for accessible treatment of optimization theory and methods with an emphasis on engineering design. Basic definitions and notations are provided in addition to the related fundamental background for linear algebra, geometry, and calculus. This new edition explores the essential topics of unconstrained optimization problems, linear programming problems, and nonlinear constrained optimization. The authors also present an optimization perspective on global search methods and include discussions on genetic algorithms, particle swarm optimization, and the simulated annealing algorithm. Featuring an elementary introduction to artificial neural networks, convex optimization, and multi-objective optimization, the Fourth Edition also offers: A new chapter on integer programming Expanded coverage of one-dimensional methods Updated and expanded sections on linear matrix inequalities Numerous new exercises at the end of each chapter MATLAB exercises and drill problems to reinforce the discussed theory and algorithms Numerous diagrams and figures that complement the written presentation of key concepts MATLAB M-files for implementation of the discussed theory and algorithms (available via the book's website) Introduction to Optimization, Fourth Edition is an ideal textbook for courses on optimization theory and methods. In addition, the book is a useful reference for professionals in mathematics, operations research, electrical engineering, economics, statistics, and business.

MATLAB Optimization Techniques

MATLAB Optimization Techniques
Author: Cesar Lopez
Publisher: Apress
Total Pages: 284
Release: 2014-11-12
Genre: Computers
ISBN: 1484202929

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.