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-reflective')

   Set properties:
               StepTolerance: 1.0000e-04

   Default properties:
                   Algorithm: 'trust-region-dogleg'
              CheckGradients: 0
                     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 Name	Current Name	Legacy Values	Current Values
`AlwaysHonorConstraints`	`HonorBounds`	`'bounds'`, `'none'`	`true`, `false`
`BranchingRule`	`BranchRule`
`CutGenMaxIter`	`CutMaxIterations`
`DerivativeCheck`	`CheckGradients`	`'on'`, `'off'`	`true`, `false`
`FinDiffRelStep`	`FiniteDifferenceStepSize`
`FinDiffType`	`FiniteDifferenceType`
`GoalsExactAchieve`	`EqualityGoalCount`
`GradConstr`	`SpecifyConstraintGradient`	`'on'`, `'off'`	`true`, `false`
`GradObj`	`SpecifyObjectiveGradient`	`'on'`, `'off'`	`true`, `false`
`Hessian`	`HessianApproximation`	`'user-supplied'`, `'bfgs'`, `'lbfgs'`, `'fin-diff-grads'`, `'on'`, `'off'`	`'bfgs'`, `'lbfgs'`, `'finite-difference'` Ignored when `HessianFcn` or `HessianMultiplyFcn` is nonempty
`HessFcn`	`HessianFcn`
`HessMult`	`HessianMultiplyFcn`
`HessUpdate` (changed in R2022a for `fminunc`)	`HessianApproximation`	`"bfgs"`, `"lbfgs"`, `{"lbfgs",Positive Integer}`, `"dfp"`, `"steepdesc"`	`"bfgs"`, `"lbfgs"`, `{"lbfgs",Positive Integer}`
`IPPreprocess`	`IntegerPreprocess`
`Jacobian`	`SpecifyObjectiveGradient`
`JacobMult`	`JacobianMultiplyFcn`
`LPMaxIter`	`LPMaxIterations`
`MaxFunEvals`	`MaxFunctionEvaluations`
`MaxIter`	`MaxIterations`
`MaxNumFeasPoints`	`MaxFeasiblePoints`
`MinAbsMax`	`AbsoluteMaxObjectiveCount`
`PlotFcns`	`PlotFcn`
`RelObjThreshold`	`ObjectiveImprovementThreshold`
`RootLPMaxIter`	`RootLPMaxIterations`
`ScaleProblem`	`ScaleProblem`	`'obj-and-constr'`, `'none'`	`true`, `false`
`SubproblemAlgorithm`	`SubproblemAlgorithm`	`'cg'`, `'ldl-factorization'`	`'cg'`, `'factorization'`
`TolCon`	`ConstraintTolerance`
`TolFun` (usage 1)	`OptimalityTolerance`
`TolFun` (usage 2)	`FunctionTolerance`
`TolFunLP`	`LPOptimalityTolerance`
`TolGapAbs`	`AbsoluteGapTolerance`
`TolGapRel`	`RelativeGapTolerance`
`TolInteger`	`IntegerTolerance`
`TolX`	`StepTolerance`

Option Names in Current Order

Current Name	Legacy Name	Current Values	Legacy Values
`AbsoluteGapTolerance`	`TolGapAbs`
`AbsoluteMaxObjectiveCount`	`MinAbsMax`
`BranchRule`	`BranchingRule`
`CheckGradients`	`DerivativeCheck`	`true`, `false`	`'on'`, `'off'`
`ConstraintTolerance`	`TolCon`
`CutMaxIterations`	`CutGenMaxIter`
`EqualityGoalCount`	`GoalsExactAchieve`
`FiniteDifferenceStepSize`	`FinDiffRelStep`
`FiniteDifferenceType`	`FinDiffType`
`FunctionTolerance`	`TolFun` (usage 2)
`HessianApproximation` for `fmincon`	`Hessian`	`'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"`
`HessianFcn`	`HessFcn`
`HessianMultiplyFcn`	`HessMult`
`HonorBounds`	`AlwaysHonorConstraints`	`true`, `false`	`'bounds'`, `'none'`
`IntegerPreprocess`	`IPPreprocess`
`IntegerTolerance`	`TolInteger`
`JacobianMultiplyFcn`	`JacobMult`
`LPMaxIterations`	`LPMaxIter`
`LPOptimalityTolerance`	`TolFunLP`
`MaxFeasiblePoints`	`MaxNumFeasPoints`
`MaxFunctionEvaluations`	`MaxFunEvals`
`MaxIterations`	`MaxIter`
`ObjectiveImprovementThreshold`	`RelObjThreshold`
`OptimalityTolerance`	`TolFun` (usage 1)
`PlotFcn`	`PlotFcns`
`RelativeGapTolerance`	`TolGapRel`
`RootLPMaxIterations`	`RootLPMaxIter`
`ScaleProblem`	`ScaleProblem`	`true`, `false`	`'obj-and-constr'`, `'none'`
`SpecifyConstraintGradient`	`GradConstr`	`true`, `false`	`'on'`, `'off'`
`SpecifyObjectiveGradient`	`GradObj` or `Jacobian`	`true`, `false`	`'on'`, `'off'`
`StepTolerance`	`TolX`
`SubproblemAlgorithm`	`SubproblemAlgorithm`	`'cg'`, `'factorization'`	`'cg'`, `'ldl-factorization'`

Current and Legacy Option Names

See Also

Topics