The previous example, lpex1.c, shows a way to copy problem data into a problem object as part of an application that calls routines from the ILOG CPLEX Callable Library. Frequently, however, a file already exists containing a linear programming problem in the industry standard MPS format, the ILOG CPLEX LP format, or the ILOG CPLEX binary SAV format. In example lpex2.c, ILOG CPLEX file-reading and optimization routines read such a file to solve the problem.

Example lpex2.c uses command line arguments to specify the name of the input file and the optimizer to call.

Where: filename is a file with extension MPS, SAV, or LP (lower case is allowed), and optimizer is one of the following letters:

For example, this command:

reads the file example.mps and solves the problem with the dual simplex optimizer.

After optimization, a call to CPXgetstat retrieves the status of the solution . The cases of infeasibility or unboundedness in the model are handled in a simple fashion here; a more complex application program might treat these cases in more detail. With these two cases out of the way, the program then calls CPXsolninfo to examine the nature of the solution. Certain that a solution exists, the application then calls CPXgetobjval to obtain the objective function value for this solution and report it.

Next, preparations are made to print the solution value and basis status of each individual variable, by allocating arrays of appropriate size; these sizes are detected by calls to the routines CPXgetnumcols and CPXgetnumrows. Note that a basis is not guaranteed to exist, depending on which optimizer was selected at run time, so some of these steps, including the call to CPXgetbase, are dependent on the solution type returned by CPXsolninfo.

The primal solution values of the variables are obtained by a call to CPXgetx, and then these values (along with the basis statuses if available) are printed, in a loop, for each variable. After that, a call to CPXgetdblquality provides a measure of the numerical roundoff error present in the solution, by obtaining the maximum amount by which any variable's lower or upper bound is violated.

You can view the complete program online in the standard distribution of the product at yourCPLEXinstallation/examples/src/lpex2.c.