Optimization Toolbox
Product Description
- Introduction and Key Features
- Defining, Solving, and Assessing Optimization Problems
- Nonlinear Programming
- Multiobjective Optimization
- Nonlinear Least-Squares, Data Fitting, and Nonlinear Equations
- Linear Programming
- Quadratic Programming
- Solving Optimization Problems Using Parallel Computing
Defining, Solving, and Assessing Optimization Problems
Optimization Toolbox includes the most widely used methods for performing minimization and maximization. The toolbox implements both standard and large-scale algorithms, enabling you to solve problems by exploiting their sparsity or structure. You can access toolbox functions and solver options with the Optimization Tool or at the command line.
An optimization routine running at the command line (left) that calls MATLAB files defining the objective function (top right) and constraint equations (bottom right).
The Optimization Tool simplifies common optimization tasks. It enables you to:
- Select a solver and define an optimization problem
- Set and inspect optimization options and their default values for the selected solver
- Run problems and visualize intermediate and final results
- View solver-specific documentation in the optional quick reference window
- Import and export problem definitions, algorithm options, and results between the MATLAB® workspace and the Optimization Tool
- Automatically generate MATLAB code to capture work and automate tasks
- Access Global Optimization Toolbox solvers
Getting Started with Optimization Tool 6:08
Set up and run optimization problems and visualize intermediate and final results.

Free Optimization Interactive Kit
Learn how to use optimization to solve systems of equations, fit models to data, or optimize system performance.
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