Minimum of single and multivariable functions, nonnegative least-squares, roots of nonlinear functions

Optimizers find the location of a minimum of a nonlinear objective function. You can find a minimum of a function of one variable on a bounded interval using fminbnd, or a minimum of a function of several variables on an unbounded domain using fminsearch. Maximize a function by minimizing its negative.

Find a nonnegative solution to a linear least-squares problem using lsqnonneg.

The equation solver fzero finds a real root of a nonlinear scalar function.

Control the output or other aspects of your optimization by setting options using optimset.


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fminbndFind minimum of single-variable function on fixed interval
fminsearchFind minimum of unconstrained multivariable function using derivative-free method
lsqnonnegSolve nonnegative linear least-squares problem
fzeroRoot of nonlinear function
optimgetOptimization options values
optimsetCreate or modify optimization options structure


Optimizing Nonlinear Functions

Minimizing and maximizing in one or more dimensions.

Curve Fitting via Optimization

This example shows how to fit a nonlinear function to data by minimizing the sum of squared errors.

Set Optimization Options

Controlling an optimization, displaying intermediate calculations.

Optimization Solver Iterative Display

Obtain intermediate output.

Optimization Solver Output Functions

Describes how to monitor or halt solvers.

Optimization Solver Plot Functions

Describes how to monitor solvers visually.

Roots of Scalar Functions

The fzero function attempts to find a root of one equation with one variable.

Optimization Troubleshooting and Tips

How to address common issues.