XSLP_OCOUNT

Number of SLP iterations over which to measure objective function variation for static objective (2) convergence criterion

Integer

5

The static objective (2) convergence criterion does not measure convergence of individual variables. Instead, it measures the significance of the changes in the objective function over recent SLP iterations. It is applied when all the variables interacting with active constraints (those that have a marginal value of at least XSLP_MVTOL) have converged. The rationale is that if the remaining unconverged variables are not involved in active constraints and if the objective function is not changing significantly between iterations, then the solution is more-or-less practical.
The variation in the objective function is defined as

δObj = MAX_Iter(Obj) - MIN_Iter(Obj)

where Iter is the XSLP_OCOUNT most recent SLP iterations and Obj is the corresponding objective function value.
If ABS(δObj) ≤ XSLP_OTOL_A
then the problem has converged on the absolute static objective (2) convergence criterion.
The static objective function (2) test is applied only if XSLP_OCOUNT is at least 2.

XSLPmaxim, XSLPminim

XSLP_OTOL_A XSLP_OTOL_R