Optimization Toolbox™ 4.0

Product Description

• Introduction and Key Features
• Defining, Solving, and Assessing Optimization Problems
• Nonlinear Optimization and Multi-Objective Optimization
• Nonlinear Least-Squares, Data Fitting, and Nonlinear Equations
• Quadratic, Linear, and Binary Integer 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 through the command-line interface or through the GUI.

An optimization routine is run at the command line (far left), and calls M-files defining the objective function (left, top) and constraint equations (left, bottom). Click on image to see enlarged view.

Optimization Tool is a graphical user interface that simplifies common optimization tasks. From the GUI, you can

• Select a solver and define your 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 your problem definitions, algorithm options, and results between the MATLAB workspace and Optimization Tool
• Automatically generate M-code to capture your work and automate tasks
• Access all Genetic Algorithm and Direct Search Toolbox™ solvers (separate license required)

An optimization routine is set up and run from the Optimization Tool GUI (far left). A user-defined output function (left, top) and selected diagnostic plots (left, bottom) show the current input point and function value for each iteration. Click on image to see enlarged view.

You can further manipulate and diagnose your optimization using the diagnostic outputs from the optimization methods. Using an output function, you can also write results to files, create your own stopping criteria, and write your own graphical user interfaces to interact with the toolbox solvers.

A user-defined output function (top) plots the current iterate at each algorithm iteration (left). The Optimization Toolbox™ also provides details for each iteration (bottom). Click on image to see enlarged view.

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