Specify optimization function options.

## Syntax

options = optimset('option1', value1, 'option2', value2, ...)

## Inputs

`optionN`
- The name of option N.
`valueN`
- The value of option N.

## Outputs

- options
- A struct containing the options.
- The available options are as follows:
- MaxIter
- The maximum number of iterations allowed.
- MaxFunEvals
- The maximum number of function evaluations allowed.
- TolFun
- The termination tolerance on the objective function convergence.
- TolX
- The termination tolerance on the parameter convergence.
- TolCon
- The constraint violation allowance, as a percent.
- TolKKT
- The termination tolerance on the Karush-Kuhn-Tucker conditions.
- GradObj
- An 'on'/'off' flag to indicate whether the objective function will return the
gradient as an optional second return value. (Only for
fminunc). The function signature is as follows:
function [sys, grad] = System(x), where
`sys`
and `grad` contain the system function and its gradient.
- GradConstr
- An 'on'/'off' flag to indicate whether the non-linear constraint function will
return the gradients as the optional third and fourth return value. If a
non-linear constraint is used, then GradConstr must be set the
same as GradObj. The function signature is as
follows: function [c, ceq, cj, ceqj] = ConFunc(x), where
`c` and `ceq` contain inequality and equality
contraints, respectively, and `cj` and `ceqj`
contain their Jacobians. The inequality constraints are assumed to have upper
bounds of 0.
- Jacobian
- An 'on'/'off' flag to indicate whether the objective function will return the
Jacobian as an optional second return value (Only for fsolve,
lsqcurvefit). The function signature is as follows:
function [res, jac] = System(x), where
`res` and
`jac` contain the residuals vector of the system function and
its Jacobian.
- Display
- An 'iter'/'off' flag to indicate whether objective function results will be
displayed at each iteration. For more extensive iteration information, see the
`output` return argument of the optimization
function.

## Examples

Set options to control the number of iterations and display intermediate
data:

`options = optimset('MaxIter', 200, 'Display', 'iter')`

```
options = struct [
Display: iter
MaxIter: 200
]
```

Set options to specify that the analytical Jacobian function name is returned by the
objective
function:

`options = optimset('Jacobian', 'on')`

```
options = struct [
Jacobian: on
]
```

## Comments

For fminbnd, the only available tolerance option is:
TolX.

For fminunc, the available tolerance options are:
TolFun and TolX.

For fminsearch, the only available tolerance option is:
TolX.

For fsolve, the available tolerance options are: TolFun
and TolX.

For fzero, the only available tolerance option is:
TolX.

For lsqcurvefit, the available tolerance options are:
TolFun and TolX.

The solver functions terminate the first time that any of the convergence tolerance
criteria are met.

The default value for MaxFunEvals is 1,000,000.

The default value for MaxIter is 400.

The default value for TolCon is 0.5.

The default value for TolFun is 1.0e-7.

The default value for TolKKT is 1.0e-4.

The default value for TolX is 1.0e-7.

For all other functions, TolX sets the convergence
criteria relative to the design variable magnitudes.

TolKKT sets the convergence criterion for the optimal relationship between
the gradients of the objective and constraint functions, which is an equation involving
Lagrange multipliers.