Preface
What Is the Optimization Toolbox?
New Features in Version 2.1
Toolbox Speed
Function Handles
Large Structured Problems
Using This Guide
Acknowledgments
Related Products
Configuration Information
Technical Conventions
Matrix, Vector, and Scalar Notation
Typographical Conventions
Tutorial
Overview
Introduction
Problems Covered by the Toolbox
Using the Optimization Functions
Examples that Use Standard Algorithms
Unconstrained Example
Nonlinear Inequality Constrained Example
Constrained Example with Bounds
Constrained Example with Gradients
Gradient Check: Analytic Versus Numeric
Equality Constrained Example
Maximization
Greater-Than-Zero Constraints
Additional Arguments: Avoiding Global Variables
Multiobjective Examples
Large-Scale Examples
Problems Covered by Large-Scale Methods
Nonlinear Equations with Jacobian
Nonlinear Equations with Jacobian Sparsity Pattern
Nonlinear Least Squares with Full Jacobian Sparsity Pattern
Nonlinear Minimization with Gradient and Hessian
Nonlinear Minimization with Gradient and Hessian Sparsity Pattern
Nonlinear Minimization with Bound Constraints and Banded Preconditioner
Nonlinear Minimization with Equality Constraints
Nonlinear Minimization with a Dense but Structured Hessian and Equality Constraints
Quadratic Minimization with Bound Constraints
Quadratic Minimization with a Dense but Structured Hessian
Linear Least Squares with Bound Constraints
Linear Programming with Equalities and Inequalities
Linear Programming with Dense Columns in the Equalities
Default Parameter Settings
Changing the Default Settings
Displaying Iterative Output
Output Headings: Medium-Scale Algorithms
Output Headings: Large-Scale Algorithms
Optimization of Inline Objects Instead of M-Files
Typical Problems and How to Deal with Them
Converting Your Code to Version 2 Syntax
Using optimset and optimget
New Calling Sequences
Example of Converting from constr to fmincon
Selected Bibliography
Standard Algorithms
Overview
Optimization Overview
Unconstrained Optimization
Quasi-Newton Methods
Line Search
Quasi-Newton Implementation
Hessian Update
Line Search Procedures
Least Squares Optimization
Gauss-Newton Method
Levenberg-Marquardt Method
Nonlinear Least Squares Implementation
Gauss-Newton Implementation
Levenberg-Marquardt Implementation
Constrained Optimization
Sequential Quadratic Programming (SQP)
Quadratic Programming (QP) Subproblem
SQP Implementation
Updating the Hessian Matrix
Quadratic Programming Solution
Line Search and Merit Function
Multiobjective Optimization
Introduction
Goal Attainment Method
Algorithm Improvements for Goal Attainment Method
Selected Bibliography
Large-Scale Algorithms
Overview
Trust Region Methods for Nonlinear Minimization
Preconditioned Conjugate Gradients
Linearly Constrained Problems
Linear Equality Constraints
Box Constraints
Nonlinear Least Squares
Quadratic Programming
Linear Least Squares
Large-Scale Linear Programming
Main Algorithm
Preprocessing
Selected Bibliography
Index of Examples
Reference
Function Reference
Functions by Category
Minimization
Equation Solving
Least Squares (Curve Fitting)
Utility
Demos of Large-Scale Methods
Demos of Medium-Scale Methods
Function Arguments
Optimization Options Parameters
Alphabetical List of Functions
fgoalattain
fminbnd
fmincon
fminimax
fminsearch
fminunc
fseminf
fsolve
fzero
linprog
lsqcurvefit
lsqlin
lsqnonlin
lsqnonneg
optimget
optimset
quadprog
Printable Documentation (PDF)
Product Page (Web)