Main Content

Current and Legacy Option Names

Many option names changed in R2016a. optimset uses only legacy option names. optimoptions accepts both legacy and current names. However, when you set an option using a legacy name-value pair, optimoptions displays the current equivalent value. For example, the legacy TolX option is equivalent to the current StepTolerance option.

options = optimoptions("fsolve",TolX=1e-4)
options = 

  fsolve options:

   Options used by current Algorithm ('trust-region-dogleg'):
   (Other available algorithms: 'levenberg-marquardt', 'trust-region')

   Set properties:
               StepTolerance: 1.0000e-04

   Default properties:
                   Algorithm: 'trust-region-dogleg'
                     Display: 'final'
    FiniteDifferenceStepSize: 'sqrt(eps)'
        FiniteDifferenceType: 'forward'
           FunctionTolerance: 1.0000e-06
      MaxFunctionEvaluations: '100*numberOfVariables'
               MaxIterations: 400
         OptimalityTolerance: 1.0000e-06
                   OutputFcn: []
                     PlotFcn: []
    SpecifyObjectiveGradient: 0
                    TypicalX: 'ones(numberOfVariables,1)'
                 UseParallel: 0

   Show options not used by current Algorithm ('trust-region-dogleg')

The following tables provide the same information. The first table lists options in alphabetical order by legacy option name, and the second table lists options in alphabetical order by current option name. The tables include only those names that differ or have different values, and show values only when they differ between legacy and current. For changes in Global Optimization Toolbox solvers, see Options Changes in R2016a (Global Optimization Toolbox).

Option Names in Legacy Order

Legacy NameCurrent NameLegacy ValuesCurrent Values
AlwaysHonorConstraintsHonorBounds"bounds", "none"true, false
FinDiffRelStepFiniteDifferenceStepSize  
FinDiffTypeFiniteDifferenceType  
GoalsExactAchieveEqualityGoalCount  
GradConstrSpecifyConstraintGradient"on", "off"true, false
GradObjSpecifyObjectiveGradient"on", "off"true, false
HessianHessianApproximation"user-supplied", "bfgs", "lbfgs", "fin-diff-grads", "on", "off"

"bfgs", "lbfgs", "finite-difference"

Ignored when HessianFcn or HessianMultiplyFcn is nonempty

HessFcnHessianFcn  
HessMultHessianMultiplyFcn  
HessUpdate (changed in R2022a for fminunc)HessianApproximation"bfgs", "lbfgs", {"lbfgs",Positive Integer}, "dfp", "steepdesc""bfgs", "lbfgs", {"lbfgs",Positive Integer}
JacobianSpecifyObjectiveGradient  
JacobMultJacobianMultiplyFcn  
MaxFunEvalsMaxFunctionEvaluations  
MaxIterMaxIterations  
MinAbsMaxAbsoluteMaxObjectiveCount  
PlotFcnsPlotFcn  
ScaleProblemScaleProblem"obj-and-constr", "none"true, false
SubproblemAlgorithmSubproblemAlgorithm"cg", "ldl-factorization""cg", "factorization"
TolConConstraintTolerance  
TolFun (usage 1)OptimalityTolerance  
TolFun (usage 2)FunctionTolerance  
TolGapAbsAbsoluteGapTolerance  
TolGapRelRelativeGapTolerance  
TolXStepTolerance  

Option Names in Current Order

Current NameLegacy NameCurrent ValuesLegacy Values
AbsoluteGapToleranceTolGapAbs  
AbsoluteMaxObjectiveCountMinAbsMax  
ConstraintToleranceTolCon  
EqualityGoalCountGoalsExactAchieve  
FiniteDifferenceStepSizeFinDiffRelStep  
FiniteDifferenceTypeFinDiffType  
FunctionToleranceTolFun (usage 2)  
HessianApproximation for fminconHessian

"bfgs", "lbfgs", "finite-difference"

Ignored when HessianFcn or HessianMultiplyFcn is nonempty

"user-supplied", "bfgs", "lbfgs", "fin-diff-grads", "on", "off"
HessianApproximation for fminunc (changed in R2022a for fminunc)HessUpdate

"bfgs", "lbfgs", {"lbfgs",Positive Integer}

"bfgs", "lbfgs", {"lbfgs",Positive Integer}, "dfp", "steepdesc"
HessianFcnHessFcn  
HessianMultiplyFcnHessMult  
HonorBoundsAlwaysHonorConstraintstrue, false"bounds", "none"
JacobianMultiplyFcnJacobMult  
MaxFunctionEvaluationsMaxFunEvals  
MaxIterationsMaxIter  
OptimalityToleranceTolFun (usage 1)  
PlotFcnPlotFcns  
RelativeGapToleranceTolGapRel  
ScaleProblemScaleProblemtrue, false"obj-and-constr", "none"
SpecifyConstraintGradientGradConstrtrue, false"on", "off"
SpecifyObjectiveGradientGradObj or Jacobiantrue, false"on", "off"
StepToleranceTolX  
SubproblemAlgorithmSubproblemAlgorithm"cg", "factorization""cg", "ldl-factorization"

See Also

Topics