e04rac initializes an empty problem with
$n$ decision variables,
$x$, and returns a handle to the data structure. This handle may then be passed to some of the functions
e04rbc,
e04rec,
e04rfc,
e04rgc,
e04rhc,
e04rjc,
e04rkc,
e04rlc,
e04rmc,
e04rnc and
e04rpc to formulate the problem (define the objective function and constraints) and to a compatible solver,
e04ffc,
e04fgc,
e04jdc,
e04jec,
e04kfc,
e04mtc,
e04ptc,
e04stc or
e04svc, to solve it. The handle
must not be changed between calls. When the handle is no longer needed,
e04rzc must be called to destroy it and deallocate all the allocated memory and data within. See
Section 4.1 in the
E04 Chapter Introduction for more details about the NAG optimization modelling suite.
None.
Not applicable.
None.
See examples associated with other functions in the suite, such as:

–the examples in Section 10 in e04ffc and Section 10 in e04fgc present a data fitting problem solved by a DFO LSQ solver,

–the examples in Section 10 in e04jdc and Section 10 in e04jec demonstrate how to use a DFO NLP solver,

–the example in Section 10 in e04kfc solves a boxconstrained nonlinear problem with a firstorder solver,

–the example in Section 10 in e04mtc solves a small LP example using an LP IPM solver,

–the example in Section 10 in e04ptc solves a small convex QCQP problem reformulated as SOCP,

–the example in Section 10 in e04rdc demonstrates how to use the SDPA file reader and how to solve linear semidefinite programming problems, including printing of the matrix Lagrangian multipliers,

–the example in Section 10 in e04rfc presents an alternative way to compute the nearest correlation matrix by means of nonlinear semidefinite programming,

–a matrix completion problem (minimization of a rank of a partially unknown matrix) formulated as SDP is demonstrated in Section 10 in e04rhc, the example also demonstrates the monitoring mode of the solver e04svc,

–the example in Section 10 in e04rjc solves LP/QP problems read in from an MPS file by e04mxc,

–an application for statistics, $E$ optimal design, solved as an SDP problem is shown in Section 10 in e04rnc,

–the example in Section 10 in e04rpc reads a BMISDP problem from a file which can be modified, in this case it solves a Static Output Feedback (SOF) problem,

–the example in Section 10 in e04rxc demonstrates how an approximate solution can be extracted during a monitoring step of e04mtc,

–the example in Section 10 in e04ryc walks through the life cycle of the handle in which a BMISDP problem is formulated and solved,

–an example in Section 10 in e04stc is a small test from Hock and Schittkowski set to show how to call the NLP solver,

–the simple example in Section 10 in e04svc demonstrates on the Lovász $\vartheta $ function eigenvalue optimization problem formulated as SDP.