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

   file Knapsack.cs
   ````````````````
   Apply a primal heuristic to a knapsack problem.
   The program demonstrates the use of the global log callback.

   We take the knapsack problem stored in burglar.mps and instigate a
   global search. At each node, so long as the current solution is
   both LP optimal and integer infeasible, we truncate the solution
   values to create a feasible integer solution. We then update the
   cutoff, if the new objective value has improved it, and continue
   the search.

   (c) 2021-2025 Fair Isaac Corporation
***********************************************************************/

using System;
using Optimizer;

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

        private void Run()
        {
            string sLogFile = "knapsack.log";
            string sProblem = "burglar";
            
            try
            {
                // initialise optimizer
                XPRS.Init("");

                prob = new XPRSprob();

                // define log file
                prob.SetLogFile(sLogFile);

                // Tell Optimizer to call OptimizerMsg whenever a message is output
                prob.AddMessageCallback(this.OptimizerMsg);

                //Turn off presolve and disallow cuts - to slow solution and allow the
                // effect of the heuristic to be seen
                prob.Presolve = 0;
                prob.CutStrategy = 0;

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

                // Prepare to apply the heuristic

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

                // Allocate memory for the coefficient arrays
                gpObjCoef = new double[gnCol];

                // Get the objective function coefficients
                prob.GetObj(gpObjCoef, 0,gnCol-1);

                // Get integer feasibility tolerance
                gdIntTol = prob.MIPTol;

                // Tell Optimizer to print global information to the log file at each node
                prob.MIPLog = 3;

                // Tell Optimizer to call truncsol at each node and apply the heuristic
                prob.AddMiplogCallback(this.TruncSol);

                // Perform the global search - in the course of which the heuristic will
                // be applied
                Console.WriteLine("Applying a primal heuristic to problem {0}",sProblem);
                prob.Optimize();
                
            }
            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)
        {
            Console.WriteLine ("{0}" + message, data);
        }

        public int TruncSol(XPRSprob prob, object data)
        {

            int nNodeNum;               // Number of nodes solved
            double dObjVal;            // Objective value
            double dCutoff;            // Cutoff value
            LPStatus nLPStatus;        // LP solution status
            int nIntInf;               // Number of integer infeasibilities
            int i;                     // Loop counter
            double dHeurObj;           // Objective value after the solution values have been truncated
            string [] sLPStatus =
            {
                    "Optimal","Infeasible","Objective worse than cutoff",
                    "Unfinished","Unbounded","Cutoff in dual"
            };


            // Get the current node number
            nNodeNum = prob.CurrentNode;
            
            // Get objective value at the current node
            dObjVal = prob.LPObjVal;

            // Get the current cutoff value
            dCutoff = prob.MIPAbsCutoff;

            // Get LP solution status and the number of integer infeasibilities
            nLPStatus = prob.LPStatus;
            nIntInf = prob.MIPInfeas;

            // Apply heuristic if nodal solution is LP optimal and integer infeasible
            if (nLPStatus == LPStatus.Optimal && nIntInf>0)
            {

                // Get LP solution
                double[] x = prob.GetCallbackSolution();
            
                // Truncate each solution value - making allowance for the integer
                //	tolerance - and calculate the new "heuristic" objective value
                for (dHeurObj=0, i=0; i<gnCol; i++)
                {
                    dHeurObj += gpObjCoef[i] * (int) (x[i] + gdIntTol);
                }
                Console.WriteLine("   Node {0}: Objective Value: ORIGINAL {1};  HEURISTIC {2}\n\n",
                                  nNodeNum,dObjVal,dHeurObj);

                // If the "heuristic" objective value is better, update the cutoff -
                //	we assume that all the objective coefficents are integers
                if( dHeurObj > dCutoff)
                {
                    prob.MIPAbsCutoff = dHeurObj + 0.9999;
                    Console.WriteLine("              ** Cutoff updated to {0} **\n\n",dHeurObj+1.0);
                }
            }

                /* If the nodal solution is not LP optimal do not apply the heuristic */
            else if (nLPStatus != LPStatus.Optimal)
            {
                Console.WriteLine("   Node {0}: LP solution not optimal, not applying heuristic\n",nNodeNum);
                Console.WriteLine("           ({0})\n\n",sLPStatus[(int)nLPStatus-1]);
            }

                /* If the nodal solution is integer feasible print the objective value */
            else if (nIntInf == 0)
            {
                Console.WriteLine("   Node {0}: Integer solution found: Objective Value {1}\n\n",
                                  nNodeNum,dObjVal);
            }

            return 0;
        }

        private XPRSprob prob;

        // converted from the C globals
        private double[] gpObjCoef;     // Objective function coefficients
        private double gdIntTol;        // Integer feasibility tolerance
        private int gnCol;              // Number of columns
    }
}