ILOG CPLEX C++ API 9.0 Reference Manual

IloCplex
IloCplex effectively treats all models as MIQCP models. That is, it allows the most
general case, although the solution algorithms make efficient use of special cases, such
as taking advantage of the absence of quadratic terms in the formulation. The method
solve begins by solving the root relaxation of the MIQCP model, where all
integrality constraints and SOSs are ignored. If the model has no integrality constraints
or SOSs, then the optimization is complete once the root relaxation is solved. Otherwise,
IloCplex uses a branch and cut procedure to reintroduce the integrality constraints or
SOSs. See the ILOG CPLEX User's Manual for more information about branch & cut.
Most users can simply call solve to solve their models. However, several parameters
are available for users who require more control. Perhaps the most important one is
IloCplex::RootAlg, which determines the algorithm used to solve the root
relaxation. Possible settings, as defined in IloCplex::Algorithm, are:
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IloCplex::Auto IloCplex automatically selects an algorithm. This is the default
setting.
IloCplex::Primal Use the primal simplex algorithm. This option is not available for
quadratically constrained problems (QCPs).
IloCplex::Dual Use the dual simplex algorithm. This option is not available for
quadratically constrained problems (QCPs).
IloCplex::Network Use network simplex on the embedded network part of the
model, followed by dual simplex on the entire model. This option is not available
for quadratically constrained problems.
IloCplex::Barrier Use the barrier algorithm.
IloCplex::Sifting Use the sifting algorithm. This option is not available for
quadratic problems. If selected nonetheless, IloCplex defaults to the
IloCplex::Auto setting.
◆ IloCplex::Concurrent Use the several algorithms concurrently. This option is not
available for quadratic problems. If selected nonetheless, IloCplex defaults to the
IloCplex::Auto setting.
Numerous other parameters allow you to control algorithmic aspects of the optimizer.
See the nested enumerations IloCplex::IntParam,
IloCplex::DoubleParam, and IloCplex#StringParam for further
information. Parameters are set with the method setParam.
Even higher levels of control can be achieved through goals (see IloCplex::Goal)
or through callbacks (see IloCplex::Callback and its extensions).
Information about a Solution
The solve method returns an IloBool value indicating whether (IloTrue) or not
(IloFalse) a solution (not necessarily the optimal one) has been found. Further
information about the solution can be queried with the method getStatus. The return
ILOG CPLEX C++ API 9.0 REFERENCE M ANUAL 48