This is machine translation

Translated by Microsoft
Mouseover text to see original. Click the button below to return to the English verison of the page.

Note: This page has been translated by MathWorks. Please click here
To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

Optimization Toolbox Product Description

Solve linear, quadratic, integer, and nonlinear optimization problems

Optimization Toolbox™ provides functions for finding parameters that minimize or maximize objectives while satisfying constraints. The toolbox includes solvers for linear programming (LP), mixed-integer linear programming (MILP), quadratic programming (QP), nonlinear programming (NLP), constrained linear least squares, nonlinear least squares, and nonlinear equations. You can define your optimization problem with functions and matrices or by specifying variable expressions that reflect the underlying mathematics.

You can use the toolbox solvers to find optimal solutions to continuous and discrete problems, perform tradeoff analyses, and incorporate optimization methods into algorithms and applications. The toolbox lets you perform design optimization tasks, including parameter estimation, component selection, and parameter tuning. It can be used to find optimal solutions in applications such as portfolio optimization, resource allocation, and production planning and scheduling.

Key Features

  • Nonlinear and multiobjective optimization of smooth constrained and unconstrained problems

  • Solvers for nonlinear least squares, constrained linear least squares, data fitting, and nonlinear equations

  • Quadratic programming (QP) and linear programming (LP)

  • Mixed-integer linear programming (MILP)

  • Optimization modeling tools

  • Graphical monitoring of optimization progress

  • Gradient estimation acceleration (with Parallel Computing Toolbox™)

Was this topic helpful?