Initializing help system before first use

# nlpvalidatekkt

Purpose
Validates the first order optimality conditions also known as the Karush-Kuhn-Tucker (KKT) conditions versus the currect solution
Synopsis
`nlpvalidatekkt(prob, mode, respectbasis, updatemult, violtarget)`
Arguments

prob | The current SLP problem.
mode | The calculation mode can be: 0 recalculate the reduced costs at the current solution using the current dual solution. 1 minimize the sum of KKT violations by adjusting the dual solution. 2 perform both.
respectbasis | The following ways are defined to assess if a constraint is active: 0 evaluate the recalculated slack activity versus XSLP_ECFTOL_R. 1 use the basis status of the slack in the linearized problem if available. 2 use both.
updatemult | The calculated values can be: 0 only used to calculate the XSLP_VALIDATIONINDEX_K measure. 1 used to update the current dual solution and reduced costs.
violtarget | When calculating the best KKT multipliers, it is possible to enforce an even distribution of reduced costs violations by enforcing a bound on them.

Return value
The input argument prob.
Parent Topic R interface reference manual

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