After the handle
has been initialized (e.g., e04rac
has been called),
may be used to declare the objective function of the problem as a nonlinear function and define the sparsity pattern (list of nonzero elements) of its gradient. If the objective function has already been defined, it will be overwritten and its Hessian (or the Hessian of the Lagrangian) will be removed. If e04rgc
is called with no nonzeroes in the sparsity pattern,
any existing objective function is removed, no new one is added and the problem will be solved as a feasible point problem.
This objective function will typically be used for nonlinear programming problems (NLP) of the kind:
The values of the nonlinear objective function
and the nonzero values of its gradient
(matching the sparsity pattern) evaluated at particular points in the decision variable space will be communicated to the NLP solver by user-supplied functions (e.g., objfun
). See Section 4.1
in the E04
Chapter Introduction for more details about the NAG optimization modelling suite.
Internal changes have been made to this function as follows:
- At Mark 27.1: Previously, it was not possible to modify the objective function once it was set or to edit the model once a solver had been called. These limitations have been removed and the associated error codes were removed.
For details of all known issues which have been reported for the NAG Library please refer to the Known Issues