Compilation and program execution

If you have followed the standard installation procedure of Xpress Optimizer, you may compile this file with the following command under Windows:

cl /MD /I%XPRESSDIR%\include %XPRESSDIR%\lib\xprs.lib folioinput.c

For Posix systems use

cc -I${XPRESSDIR}/include -L${XPRESSDIR}/lib folioinput.c -o folioinput -lxprs

For other systems please refer to the example makefile provided with the corresponding distribution.

If we run this program with the matrix Folio.mat for the LP example problem of Chapter 2, then we obtain an output file Folio.prt with the following contents:

Problem Statistics
Matrix FolioLP
Objective *OBJ*

RHS *RHS*
Problem has      4 rows and     10 structural columns

Solution Statistics
Maximization performed
Optimal solution found after      5 iterations
Objective function value is    14.066659

Rows Section
   Number    Row     At     Value      Slack Value   Dual Value      RHS
 N      1  *OBJ*     BS    14.066659    -14.066659       .000000     .000000
 E      2  Cap       EQ     1.000000       .000000      8.000000    1.000000
 G      3  NA        LL      .500000       .000000     -5.000000     .500000
 L      4  Risk      UL      .333333       .000000     23.000000     .333333

Columns Section
   Number   Column   At     Value      Input Cost   Reduced Cost
 C      5  frac      UL      .300000      5.000000      2.000000
 C      6  frac_1    LL      .000000     17.000000     -9.000000
 C      7  frac_2    BS      .200000     26.000000       .000000
 C      8  frac_3    LL      .000000     12.000000    -14.000000
 C      9  frac_4    BS      .066667      8.000000       .000000
 C     10  frac_5    UL      .300000      9.000000      1.000000
 C     11  frac_6    LL      .000000      7.000000     -1.000000
 C     12  frac_7    LL      .000000      6.000000     -2.000000
 C     13  frac_8    BS      .133333     31.000000       .000000
 C     14  frac_9    LL      .000000     21.000000    -10.000000      

The upper half contains some statistics concerning the problem size and the solution algorithm: the optimal LP solution found has a value of 14.066659. The Rows Section gives detailed solution information for the constraints in the problem. The solution values for the decision variables are located in the column labeled Value of the Columns Section.