Book description
MATLAB is a highlevel 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 builtin 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 handson 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 MATLABs Optimization Toolbox, which implements stateoftheart algorithms for solving multiobjective problems, nonlinear minimization with boundary conditions and restrictions, minimax optimization, semiinfinitely constrained minimization and linear and quadratic programming. A wide range of exercises and examples are included, illustrating the most widely used optimization methods.
Table of contents
 Cover
 Title
 Copyright
 Contents at a Glance
 Contents
 About the Author
 Chapter 1: Introducing MATLAB and the MATLAB Working Environment

Chapter 2: MATLAB Programming

2.1 MATLAB Programming
 2.1.1 The Text Editor
 2.1.2 Scripts
 2.1.3 Functions and Mfiles. Eval and Feval
 2.1.4 Local and Global Variables
 2.1.5 Data Types
 2.1.6 Flow Control: FOR, WHILE and IF ELSEIF Loops
 2.1.7 Subfunctions
 2.1.8 Commands in Mfiles
 2.1.9 Functions Relating to Arrays of Cells
 2.1.10 Multidimensional Array Functions

2.1 MATLAB Programming
 Chapter 3: Basic MATLAB Functions for Linear and NonLinear Optimization
 Chapter 4: Optimization by Numerical Methods: Solving Equations
 Chapter 5: Optimization Using Symbolic Computation

Chapter 6: Optimization Techniques Via The Optimization Toolbox
 6.1 The Optimization Toolbox

6.2 Minimization Algorithms
 6.2.1 Multiobjective Problems
 6.2.2 NonLinear Scalar Minimization With Boundary Conditions
 6.2.3 NonLinear Minimization with Restrictions
 6.2.4 Minimax Optimization: fminimax and fminuc
 6.2.5 Minimax Optimization
 6.2.6 Minimum Optimization: fminsearch and fminuc
 6.2.7 SemiInfinitely Constrained Minimization
 6.2.8 Linear Programming
 6.2.9 Quadratic programming
 6.3 Equation Solving Algorithms
 6.4 Fitting Curves by Least Squares

Chapter 7: Differentiation in one and Several Variables. Applications to Optimization
 7.1 Derivatives
 7.2 Par?tial Derivatives
 7.3 Applications of Derivatives. Tangents, Asymptotes, Extreme Points and Turning Points
 7.4 Differentiation of Functions of Several Variables
 7.5 Maxima and Minima of Functions of Several Variables
 7.6 Conditional Minima and Maxima. The Method of “Lagrange Multipliers”
 7.7 Vector Differential Calculus
 7.8 The Composite Function Theorem
 7.9 The Implicit Function Theorem
 7.10 The Inverse Function Theorem
 7.11 The Change of Variables Theorem
 7.12 Series Expansions in Several Variables
 7.13 Vector Fields. Curl, Divergence and the Laplacian
 Spherical, Cylindrical and Rectangular Coordinates

Chapter 8: Optimization of Functions of Complex Variables
 8.1 Complex Numbers
 8.2 General Functions of a Complex Variable
 8.3 Specific Functions of a Complex Variable
 8.4 Basic Functions with Complex Vector Arguments
 8.5 Basic Functions with Complex Matrix Arguments
 8.6 General Functions with Complex Matrix Arguments
 8.7 Matrix Operations with Real and Complex Variables
 Chapter 9: Algebraic Expressions, Polynomials, Equations and Systems. Tools for Optimization
Product information
 Title: MATLAB Optimization Techniques
 Author(s):
 Release date: November 2014
 Publisher(s): Apress
 ISBN: 9781484202920
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