declarations
 Profit:linctr
end-declarations
	  	
maximize(XPRS_DUAL+XPRS_LPSTOP, Profit)  

declarations
 MinCost:linctr
end-declarations
	  	
minimize(XPRS_BAR+XPRS_LIN, MinCost) 

1. This procedure calls the Optimizer to maximize/minimize the current problem (excluding all hidden constraints) using the given constraint as objective function. Optionally, the algorithm to be used can be defined. By default, the global search is executed automatically if the problem contains any global entities. Where appropriate, several algorithm choice parameters may be combined (using plus signs).

2. If XPRS_LIN is specified, then the discreteness of all global entities is ignored, even during the presolve procedure.

3. If XPRS_LPSTOP is specified, then just the LP at the top node is solved and no Branch-and-Bound search is initiated. But the discreteness of the global entities is taken into account in presolving the LP at the top node. Note also that getprobstat still returns information related to the MIP problem when this option is used although only an LP solve has been executed and the solution information returned by getsol corresponds to the current LP solution. However, if the the MIP is solved to optimality during this call, the MIP optimal solution will be returned by getsol.

4. If XPRS_CONT is used after a solve has completed, the routine returns immediately without altering the current problem status.

5. If XPRS_ENUM is specified, the optimiser starts a search for the n-best MIP solutions. The maximum number of solutions to store may be specified using the XPRS_enummaxsol (default: 10). After the execution of the enumeration, the number of solutions found during the search is returned by the control parameter XPRS_enumsols. The procedure selectsol can then be used to select one of these solutions.

6. If XNLP_LOCAL is specified for a non-linear problem having been loaded using mmxnlp and which have been solved using XSLP, then the current linearization will be reoptimized.

7. If XPRS_TUNE is specified the problem will be tuned and then solved with the best control settings identified by the tuner. For a user guide about the tuner, please refer to the documentation of the Xpress Optimizer.

8. If XNLP_CORELP is specified for a non-linear problem having been loaded using mmxnlp, then only the linear part of the problem will be loaded and optimized. This is usefull for checking if the linear part of the problem is well posed.

9. Support for quadratic programming requires the module mmnl.

10. Support for general nonlinear programming requires the module mmxnlp.

11. Support for robust programming requires the module mmrobust.