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.

What you’ll learn

• The MATLAB environment and MATLAB programming.

• How to solve equations and systems of equations with MATLAB.

• The main features of MATLAB's Optimization Toolbox, which implements state-of-the art algorithms for solving optimization problems.

• How to use MATLAB for multivariate calculus.

• A wide range of optimization techniques, augmented with numerous examples and exercises.

Who this book is for

This book is for anyone who wants to work on optimization problems in a practical, hands-on manner using MATLAB. You'll already have a core understanding of undergraduate level calculus, and have access to an installed version of MATLAB, but no previous experience of MATLAB is assumed.

Table of Contents

1. Introduction to the MATLAB Environment

2. Programming with MATLAB Variables, Numbers, Operators, and Functions

3. Introducing the MATLAB Optimization Toolbox – Linear and Non-Linear Functions

4. Optimized Algorithms for Numerical Calculation Equations

5. Optimizations using Symbolic Computation

6. Core Optimization Techniques through the MATLAB Optimization Toolbox

7. Differentiation in One and Several Variables

8. Optimization in Complex Variables

9. Optimizing Algebraic Expressions, Polynomials, Equations and Systems