Tolerances and Stopping Criteria
The number of iterations in an optimization depends on a solver's stopping criteria. These criteria include several tolerances you can set. Generally, a tolerance is a threshold which, if crossed, stops the iterations of a solver.
Set tolerances and other criteria using
optimoptions as explained in Set and Change Optimization Options.
Generally set tolerances such as
StepTolerance to be well above
1e-14. Setting small tolerances does not always
result in accurate results. Instead, a solver can fail to recognize when it has
converged, and can continue futile iterations. A tolerance value smaller than
eps effectively disables that stopping condition. This tip
does not apply to
fzero, which uses a default value of
eps for the
optimoptions displays tolerances. For
options = optimoptions('fmincon'); [options.OptimalityTolerance,options.FunctionTolerance,options.StepTolerance]
ans = 1.0e-06 * 1.0000 1.0000 0.0001
You can also find the default tolerances in the options section of the solver function reference page.
StepToleranceis a lower bound on the size of a step, meaning the norm of (xi – xi+1). If the solver attempts to take a step that is smaller than
StepTolerance, the iterations end.
StepToleranceis generally used as a relative bound, meaning iterations end when |(xi – xi+1)| <
StepTolerance*(1 + |xi|), or a similar relative measure. See Tolerance Details.
For some algorithms,
FunctionToleranceis a lower bound on the change in the value of the objective function during a step. For those algorithms, if |f(xi) – f(xi+1)| <
FunctionTolerance, the iterations end.
FunctionToleranceis generally used as a relative bound, meaning iterations end when |f(xi) – f(xi+1)| <
FunctionTolerance*(1 + |f(xi)|), or a similar relative measure. See Tolerance Details.
Unlike other solvers,
fminsearchstops when it satisfies both
TolFun(the function tolerance) and
TolX(the step tolerance).
OptimalityToleranceis a tolerance for the first-order optimality measure. If the optimality measure is less than
OptimalityTolerance, the iterations end.
OptimalityTolerancecan also be a relative bound on the first-order optimality measure. See Tolerance Details. First-order optimality measure is defined in First-Order Optimality Measure.
ConstraintToleranceis an upper bound on the magnitude of any constraint functions. If a solver returns a point x with c(x) >
ConstraintToleranceor |ceq(x)| >
ConstraintTolerance, the solver reports that the constraints are violated at x.
ConstraintTolerancecan also be a relative bound. See Tolerance Details.
ConstraintToleranceoperates differently from other tolerances. If
ConstraintToleranceis not satisfied (i.e., if the magnitude of the constraint function exceeds
ConstraintTolerance), the solver attempts to continue, unless it is halted for another reason. A solver does not halt simply because
MaxIterationsis a bound on the number of solver iterations.
MaxFunctionEvaluationsis a bound on the number of function evaluations. Iterations and function evaluations are discussed in Iterations and Function Counts.
There are two other tolerances that apply to particular solvers:
MaxPCGIter. These relate to
preconditioned conjugate gradient steps. For more information, see Preconditioned Conjugate Gradient Method.
There are several tolerances that apply only to the
interior-point algorithm. For more information, see Interior-Point
There are several tolerances that apply only to
Some “Integer” Solutions Are Not Integers and Branch and Bound.