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| R2011b Documentation → Optimization Toolbox | |
Learn more about Optimization Toolbox |
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| Contents | Index |
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Optimization Toolbox provides widely used algorithms for standard and large-scale optimization. These algorithms solve constrained and unconstrained continuous and discrete problems. The toolbox includes functions for linear programming, quadratic programming, binary integer programming, nonlinear optimization, nonlinear least squares, systems of nonlinear equations, and multiobjective optimization. You can use them to find optimal solutions, perform tradeoff analyses, balance multiple design alternatives, and incorporate optimization methods into algorithms and models.
Key features:
Interactive tools for defining and solving optimization problems and monitoring solution progress
Solvers for nonlinear and multiobjective optimization
Solvers for nonlinear least squares, data fitting, and nonlinear equations
Methods for solving quadratic and linear programming problems
Methods for solving binary integer programming problems
Parallel computing support in selected constrained nonlinear solvers
Most toolbox functions are MATLAB® function files, made up of MATLAB statements that implement specialized optimization algorithms. You can view the code for these functions using the statement
type function_name
You can extend the capabilities of Optimization Toolbox software by writing your own functions, or by using the software in combination with other toolboxes, or with the MATLAB or Simulink® environments.
Optimization Tool (optimtool) is a graphical user interface (GUI) for selecting a toolbox function, specifying optimization options, and running optimizations. It provides a convenient interface for all optimization routines, including those from Global Optimization Toolbox software, which is licensed separately.
Optimization Tool makes it easy to
Define and modify problems quickly
Use the correct syntax for optimization functions
Import and export from the MATLAB workspace
Generate code containing your configuration for a solver and options
Change parameters of an optimization during the execution of certain Global Optimization Toolbox functions
 | Getting Started | Example: Nonlinear Constrained Minimization |  |
Learn how to use optimization to solve systems of equations, fit models to data, or optimize system performance.
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