MATLAB OPTIMIZATION TOOLBOX - RELEASE NOTES Manuel d'utilisateur télécharger pdf (Page 32)

R2012a

7-2

Enhanced Robustness in fminunc

The fminunc medium-scale algorithm now attempts to recover from failures when

evaluating the objective function during iteration steps, or during gradient estimation.

Failure means the objective function returns NaN, a complex value, or Inf. If there is

such a failure, the algorithm attempts to take different steps.

As part of robustness, the fminunc medium-scale algorithm now uses the

ObjectiveLimit tolerance.

Compatibility Considerations

When objective function values drop below ObjectiveLimit (default value: -1e20),

iterations end with a -3 exit flag. Use optimset to change the value of ObjectiveLimit.

Set ObjectiveLimit to -Inf to disable this tolerance.

FinDiffRelStep Option in Optimization Tool

The FinDiffRelStep option for choosing relative finite difference step sizes is now

available in the Optimization Tool, in the Approximated derivatives pane. This option

lets you tune the gradient estimation step in most solvers.

Levenberg-Marquardt Algorithm Tweak

The fsolve, lsqcurvefit, and lsqnonlin solvers no longer use the magnitude of the

Levenberg-Marquardt regularization parameter as a stopping criterion, so they no longer

return an exit flag of -3 when using the levenberg-marquardt algorithm. Instead,

they use the TolX tolerance in all internal calculations.

Compatibility Considerations

The solvers now stop with exit flag 2 in most situations where previously they stopped

with exit flag -3.

fmincon sqp Algorithm Tweak

The fmincon sqp algorithm calculates its Lagrange multiplier estimates somewhat

differently than before.

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MATLAB OPTIMIZATION TOOLBOX - RELEASE NOTES Manuel d'utilisateur Page 32