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Load an LP and modify it by adding an extra constraint

Description
The problem
               Maximize
2x + y
subject to
c1:  x + 4y <= 24
c2:       y <=  5
c3: 3x +  y <= 20
c4:  x +  y <=  9
and
0 <= x,y <= +infinity
and the extra constraint
               c5: 6x + y <= 20
are first stored in the user's data structures. The LP is then loaded into Optimizer, using loadprob, and solved using the primal simplex algorithm. Next, the extra constraint is added to the problem matrix, using addrows, and the revised problem solved using the dual algorithm. In each case, the problem matrix is output to a file, the objective function value displayed on screen, and the problem statistics are are stored in a log file.

 loadlp_dnet.zip [download all files]

Source Files
By clicking on a file name, a preview is opened at the bottom of this page.
 LoadLP.cs [download] LoadLP.csproj [download]

LoadLP.cs

/***********************************************************************
Xpress Optimizer Examples
=========================

file LoadLP.cs

Load an LP problem directly into Optimizer and modify it by adding an
extra constraint.

The problem
Maximise
2x + y
subject to
c1:  x + 4y <= 24
c2:       y <=  5
c3: 3x +  y <= 20
c4:  x +  y <=  9
and
0 <= x, y <= +infinity
and the extra constraint
c5: 6x + y <= 20
are first stored in the user's data structures. The LP is then loaded
into Optimizer, using loadprob, and solved using the primal simplex
algorithm. Next, the extra constraint is added to the problem matrix,
using addrows, and the revised problem solved using the dual algorithm.
In each case, the problem matrix is output to a file, the objective
function value displayed on screen, and the problem statistics are
are stored in a log file.

(c) 2021 Fair Isaac Corporation
***********************************************************************/

using System;
using Optimizer;

namespace XPRSExamples
{
class LoadLP
{
public static void Main(string[] args)
{
LoadLP example = new LoadLP();
example.Run();
}

private void Run()
{

// Store the problem
// Row data
int nRow = 4;
char[] sRowType = {'L', 'L', 'L', 'L'};
double[] dRHS = { 24.0, 5.0, 20.0, 9.0 };
string[] sRowName = { "c1", "c2", "c3", "c4"  };

// Column data
int nCol = 2;
double[] dObj = { 2.0, 1.0 };
double[] dLowerBd = { 0,0};
double[] dUpperBd = { XPRS.PLUSINFINITY, XPRS.PLUSINFINITY };

string[] sColName = { "x", "y" };

// Matrix data
int[] nColStart = { 0,3,7 };
int[] nRowInd = {0,2,3,0,1,2,3 };
double[] dMatElem = { 1,3,1,4,1,1,1 };

// Store extra constraint
int nNewRow = 1;
int nNewElem = 2;
char[] sNewRowType = {'L'};
string[] sNewRowName = {"c5"};

double[] dNewRHS = {20};
double[] dNewRowElem = { 6,1 };
int[] nNewRowStart = { 0,2 };
int[] nNewColInd = { 0,1 };

double dObjValue;

string sLogFile = "loadlp.log";
string sProblem1 = "lp";
string sProblem2 = "revised";

try
{
XPRS.Init("");

prob = new XPRSprob();
prob.SetLogFile(sLogFile);

// Tell Optimizer to call OptimizerMsg whenever a message is output
prob.MessageCallbacks += new MessageCallback (this.OptimizerMsg);

prob.LoadLP(sProblem1, nCol, nRow, sRowType, dRHS, null, dObj, nColStart, null, nRowInd, dMatElem, dLowerBd, dUpperBd);
prob.ChgObjSense(ObjSense.Maximize);

// Add row names
prob.AddNames(1, sRowName, 0, nRow -1 );

// Add column names
prob.AddNames(2, sColName, 0, nCol -1 );

// Output the matrix
prob.WriteProb(sProblem1, "");

// Solve the LP problem
prob.LpOptimize();

// Get and display the value of the objective function
dObjValue = prob.LPObjVal;
Console.WriteLine("The optimal objective value is {0}", dObjValue);

// ** Add the extra constraint and solve again **

// Add new row
prob.AddRows(nNewRow, nNewElem, sNewRowType, dNewRHS, null, nNewRowStart, nNewColInd, dNewRowElem);

// Add new row name
prob.AddNames(1, sNewRowName, nRow, nRow);

// Output the revised matrix
prob.WriteProb(sProblem2, "");
Console.WriteLine("Matrix file {0}.mat has been created", sProblem2);

// Solve with dual - since the revised problem inherits dual feasibility
// from the original
prob.LpOptimize("d");

// Get and display the value of the objective function
dObjValue = prob.LPObjVal;
Console.WriteLine("The revised optimal objective value is {0}",dObjValue);

}

catch (XPRSException e)
{
Console.WriteLine(e.ToString());
throw e;
}
finally
{
prob.Destroy();
XPRS.Free();
}
}

public void OptimizerMsg (XPRSprob prob, object data, string message, int len, int msglvl)
{
switch(msglvl)
{
case 3:
case 4:
Console.WriteLine ("{0}" + message, data);
break;
}
}

private XPRSprob prob;
}
}