After the model has been fully or partially built by calling functions of the NAG optimization modelling suite,
e04rcc may be used to change properties of a subset of the variables in the model. The property is given by
ptype which
refers to the
integrality of the variables (
continuous, integer or
binary) or their
linearity (if the variables are
linear or
generic, see
Section 3.1). Both classes of properties can be set independently, however, only one property per class of properties can be chosen (i.e., a variable can be linear and integer but it cannot be continuous and binary at the same time). The properties can be changed multiple times and the last setting is the one used.
e04ryc may be used to display the properties and further details of the problem.
See
Section 4.1 in the
E04 Chapter Introduction for more details about the NAG optimization modelling suite.
It is sometimes useful in Nonlinear Programming (NLP) problems to distinguish between linear and nonlinear variables and thus give the solvers an extra piece of information to utilize. A variable is said to be linear if its involvement in the whole optimization model is linear, i.e., it appears only in linear expressions. All other variables, if used at all, are nonlinear.
Let's assume that we have a problem with seven variables with two nonlinear constraints declared by
e04rkc and defined as follows:
and with a linear objective function, linear constraints. Variables
${x}_{6}$ and
${x}_{7}$ are not used at all in the definition of
$g\left(x\right)$ and, therefore, they are clearly linear which is automatically detected by the solver. Although
${x}_{1}$ and
${x}_{5}$ appear in the nonlinear constraints
$g\left(x\right)$, they are involved only in linear expressions and, therefore, are also linear. These two cannot be detected by the solver because the solver can only see the sparsity pattern defined by
e04rkc and a Black Box call-back. In this case, it might be beneficial to set their property as
linear using this function. If no property is set, it is assumed that the variables are
generic, meaning that they have no special property, and their linearity is auto detected based on the constraints they appear in.
Solvers which can exploit this property will describe it in their documentation.
None.
Not applicable.
Please consult the
X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the
Users' Note for your implementation for any additional implementation-specific information.
None.