Apply a binary fixing heuristic to an unpresolved MIP problem

We take a production plan model and solve its LP relaxation.
Next we fix those binary variables that are very near zero to 0.0, and those that are almost one to 1.0, by changing their respective upper and lower bounds. Finally, we solve the modified problem as a MIP.

This heuristic will speed up solution - though may fail to optimse the problem.

The results are displayed on screen and the problem statistics stored in a log file.

using System;
using System.IO;
using Optimizer;


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

		private const double TOL=0.0005;            // Tolerance on binary variables

		private void Run()
		{	
			try
			{
				string sProblem=@"..\..\..\Data\coco";      // Problem name
				string sLogFile="fixbv.log"; // Log file name

				int nCol;                    // Number of columns

				// Global problem information
				int nGlEnt;                  // Number of global entities: binary, integer, semi-continuous and partial integer variables
				int nSet;                    // Number of S1 and S2 sets
				int[] pGlInd;                 // Column indices of the global entities
				char[] pGlType;               // Global entity types

				// Bound changes
				int[] pBndInd;                // Column indices of the bounds to be changed
				char[] pBndType;              // New bound type
				double[] pBndVal;             // New bound values
				int nBnd;                    // Bound counter
				int i;                       // Loop counter
				int j;                       // Holder for the bound indices

				// Solution information
				double[] x;                  // LP solution values
				int nGlStatus;               // Global status
				int nNodes;                  // Number of nodes solved so far in the global search
				double dObjVal;              // Objective value of the best integer solution

				// Initialise Optimizer
				XPRS.Init("");
				Console.Write(XPRS.GetBanner());

				prob = new XPRSprob();

				// Delete and define log file
				// Delete the file if it exists.
				if (File.Exists(sLogFile)) 
				{
					File.Delete(sLogFile);
				}
				prob.SetLogFile(sLogFile);

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

				// Get and display the Optimizer version number
				Console.WriteLine("\nXpress Optimiser Subroutine Library Release {0}\n\n", prob.Version/100);

				// Turn off presolve and permit no cuts - to slow down solution and allow
				// the effect of the heuristic to be be seen
				prob.Presolve = 0;
				prob.CutStrategy = 0;

				// Read the problem file
        prob.MPSFormat = -1;
				prob.ReadProb(sProblem,"");

				// Solve the LP relaxation

				// Get the number of columns
				nCol = prob.Cols;

				// Allocate memory for solution array and check for memory shortage
				x= new double[nCol];
				
				// Solve the LP
				prob.Maxim("");
		
				// Get LP solution values
				prob.GetSol(x,null,null,null);

				// Fix the binary variables that are at their bounds

				// Allocate memory for global entity arrays
				pGlInd = new int[nCol];
				pGlType = new char[nCol];

				// Get global entity information

				prob.GetGlobal(out nGlEnt, out nSet, pGlType, pGlInd, null, null, (int[])null, null, null);

				// Allocate memory for bound arrays 
				pBndInd = new int[nGlEnt];
				pBndVal = new double[nGlEnt];
				pBndType = new char[nGlEnt];

				// Initialise bound counter
				nBnd=0;

				// Go through the global entities
				for(i=0; i