Optimization Toolbox

optimset

Create or edit optimization options parameter structure.

Syntax

• options = optimset('param1',value1,'param2',value2,...)
  optimset
  options = optimset
  options = optimset(optimfun)
  options = optimset(oldopts,'param1',value1,...)
  options = optimset(oldopts,newopts)
  

Description

options = optimset('param1',value1,'param2',value2,...) creates an optimization options parameter structure called options, in which the specified parameters (param) have specified values. Any unspecified parameters are set to [] (parameters with value [] indicate to use the default value for that parameter when options is passed to the optimization function). It is sufficient to type only enough leading characters to define the parameter name uniquely. Case is ignored for parameter names.

optimset with no input or output arguments displays a complete list of parameters with their valid values.

options = optimset (with no input arguments) creates an options structure options where all fields are set to [].

options = optimset(optimfun) creates an options structure options with all parameter names and default values relevant to the optimization function optimfun.

options = optimset(oldopts,'param1',value1,...) creates a copy of oldopts, modifying the specified parameters with the specified values.

options = optimset(oldopts,newopts) combines an existing options structure oldopts with a new options structure newopts. Any parameters in newopts with nonempty values overwrite the corresponding old parameters in oldopts.

Parameters

For more information about individual parameters, see the reference pages for the optimization functions that use these parameters, or Optimization Parameters.

In the lists below, values in { } denote the default value; some parameters have different defaults for different optimization functions and so no values are shown in { }. 

You can also view the optimization parameters and defaults by typing optimset at the command line.

Optimization parameters used by both large-scale and medium-scale algorithms:

Diagnostics	'on' | {'off'}
Display	'off' | 'iter' | 'final' | 'notify'
GradObj	'on' | {'off'}
Jacobian	'on' | {'off'}
LargeScale	'on' |'off'. The default for fsolve is 'off'. The default for all other functions that provide a large-scale algorithm is 'on'.
MaxFunEvals	positive integer
MaxIter	positive integer
TolCon	positive scalar
TolFun	positive scalar
TolX	positive scalar

Optimization parameters used by large-scale algorithms only:

Hessian	'on' | {'off'}
HessMult	function | {[]}
HessPattern	sparse matrix |{sparse matrix of all ones}
JacobMult	function | {[]}
JacobPattern	sparse matrix |{sparse matrix of all ones}
MaxPCGIter	positive integer | {the greater of 1 and floor(n/2))} where n is the number of elements in x0, the starting point
PrecondBandWidth	positive integer | {0}  | Inf
TolPCG	positive scalar | {0.1}
TypicalX	vector of all ones

Optimization parameters used by medium-scale algorithms only:

DerivativeCheck	'on' | {'off'}
DiffMaxChange	positive scalar | {1e-1}
DiffMinChange	positive scalar | {1e-8}
GoalsExactAchieve	positive scalar integer | {0}
GradConstr	'on' | {'off'}
HessUpdate	{'bfgs'} | 'dfp' | 'gillmurray' | 'steepdesc'
LevenbergMarquardt	'on' | {'off'}
LineSearchType	'cubicpoly' | {'quadcubic'}
MeritFunction	'singleobj' | {'multiobj'}
MinAbsMax	positive scalar integer | {0}
NonlEqnAlgorithm	{'dogleg'} | 'lm' | 'gn', where 'lm' is Levenburg-Marquardt and 'gn' is Gauss-Newton.

Examples

This statement creates an optimization options structure called options in which the Display parameter is set to 'iter' and the TolFun parameter is set to 1e-8.

• options = optimset('Display','iter','TolFun',1e-8)
  

This statement makes a copy of the options structure called options, changing the value of the TolX parameter and storing new values in optnew.

• optnew = optimset(options,'TolX',1e-4);
  

This statement returns an optimization options structure options that contains all the parameter names and default values relevant to the function fminbnd.

• options = optimset('fminbnd')
  

If you only want to see the default values for fminbnd, you can simply type

• optimset fminbnd
  

or equivalently

• optimset('fminbnd')
  

See Also
optimget

optimget

quadprog