public static void Main(string[] args)
{
if (args.Length != 1)
{
System.Console.WriteLine("Usage: Goalex1 filename");
System.Console.WriteLine(" where filename is a file with extension ");
System.Console.WriteLine(" MPS, SAV, or LP (lower case is allowed)");
System.Console.WriteLine(" Exiting...");
return;
}
try {
Cplex cplex = new Cplex();
cplex.ImportModel(args[0]);
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
cplex.SetParam(Cplex.Param.MIP.Strategy.Search, Cplex.MIPSearch.Traditional);
if (cplex.Solve(new MyBranchGoal(lp.NumVars)))
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught: " + e);
}
}
internal static ILPMatrix PopulateByRow(IMPModeler model)
{
ILPMatrix lp = model.AddLPMatrix();
double[] lb = { 0.0, 0.0, 0.0 };
double[] ub = { 40.0, System.Double.MaxValue, System.Double.MaxValue };
INumVar[] x = model.NumVarArray(model.ColumnArray(lp, 3), lb, ub);
// - x0 + x1 + x2 <= 20
// x0 - 3*x1 + x2 <= 30
double[] lhs = { -System.Double.MaxValue, -System.Double.MaxValue };
double[] rhs = { 20.0, 30.0 };
double[][] val = { new double[] { -1.0, 1.0, 1.0 },
new double[] { 1.0, -3.0, 1.0 } };
int[][] ind = { new int[] { 0, 1, 2 },
new int[] { 0, 1, 2 } };
lp.AddRows(lhs, rhs, ind, val);
// Q = 0.5 ( 33*x0*x0 + 22*x1*x1 + 11*x2*x2 - 12*x0*x1 - 23*x1*x2 )
INumExpr x00 = model.Prod(33.0, model.Square(x[0]));
INumExpr x11 = model.Prod(22.0, model.Square(x[1]));
INumExpr x22 = model.Prod(11.0, model.Square(x[2]));
INumExpr x01 = model.Prod(-12.0, model.Prod(x[0], x[1]));
INumExpr x12 = model.Prod(-23.0, model.Prod(x[1], x[2]));
INumExpr Q = model.Prod(0.5, model.Sum(x00, x11, x22, x01, x12));
// maximize x0 + 2*x1 + 3*x2 + Q
double[] objvals = { 1.0, 2.0, 3.0 };
model.Add(model.Maximize(model.Diff(model.ScalProd(x, objvals), Q)));
return(lp);
}
internal static void SolveAndDisplay(Cplex cplex, ILPMatrix lp)
{
if (cplex.Solve())
{
double[] x = cplex.GetValues(lp);
double[] dj = cplex.GetReducedCosts(lp);
double[] pi = cplex.GetDuals(lp);
double[] slack = cplex.GetSlacks(lp);
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.GetObjValue());
int nvars = x.Length;
for (int j = 0; j < nvars; ++j)
{
System.Console.WriteLine("Variable " + j + ": Value = " + x[j] + " Reduced cost = " + dj[j]);
}
int ncons = slack.Length;
for (int i = 0; i < ncons; ++i)
{
System.Console.WriteLine("Constraint " + i + ": Slack = " + slack[i] + " Pi = " + pi[i]);
}
}
}
// To populate by row, we first create the variables, and then use them to
// create the range constraints and objective. The model we create is:
//
// Minimize
// obj: - 0.5 (-3 * xˆ2 - 3 * yˆ2 - 1 * x * y)
// Subject To
// c1: -x + y >= 0
// c2: x + y >= 0
// Bounds
// -1 <= x <= 1
// 0 <= y <= 1
// End
internal static ILPMatrix PopulateByRow(IMPModeler model)
{
ILPMatrix lp = model.AddLPMatrix();
double[] lb = { -1.0, 0.0 };
double[] ub = { 1.0, 1.0 };
INumVar[] x = model.NumVarArray(model.ColumnArray(lp, 2), lb, ub);
double[] lhs = { 0.0, 0.0 };
double[] rhs = { System.Double.MaxValue, System.Double.MaxValue };
double[][] val = { new double[] { -1.0, 1.0 },
new double[] { 1.0, 1.0 } };
int[][] ind = { new int[] { 0, 1 },
new int[] { 0, 1 } };
lp.AddRows(lhs, rhs, ind, val);
INumExpr x00 = model.Prod(-3.0, x[0], x[0]);
INumExpr x11 = model.Prod(-3.0, x[1], x[1]);
INumExpr x01 = model.Prod(-1.0, x[0], x[1]);
INumExpr Q = model.Prod(0.5, model.Sum(x00, x11, x01));
model.Add(model.Minimize(Q));
return(lp);
}
public static void Main(string[] args)
{
try {
Cplex cplex = new Cplex();
ILPMatrix lp = PopulateByRow(cplex);
int[] ind = { 0 };
double[] val = { 1.0 };
// When a non-convex objective function is present, CPLEX
// will raise an exception unless the parameter
// Cplex.Param.SolutionTarget is set to accept
// first-order optimal solutions
cplex.SetParam(Cplex.Param.SolutionTarget, 2);
// CPLEX may converge to either local optimum
SolveAndDisplay(cplex, lp);
// Add a constraint that cuts off the solution at (-1, 1)
lp.AddRow(0.0, System.Double.MaxValue, ind, val);
SolveAndDisplay(cplex, lp);
// Remove the newly added constraint and add a new constraint
// with the opposite sense to cut off the solution at (1, 1)
lp.RemoveRow(lp.Nrows - 1);
lp.AddRow(-System.Double.MaxValue, 0.0, ind, val);
SolveAndDisplay(cplex, lp);
cplex.ExportModel("indefqpex1.lp");
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception '" + e + "' caught");
}
}
// Modifying all quadratic terms x[i]*x[j]
// in the objective function.
internal static void ModifyQuadObjective(CplexModeler model)
{
IEnumerator matrixEnum = model.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
INumVar[] x = lp.NumVars;
int ncols = x.Length;
IObjective obj = model.GetObjective();
// Note that the quadratic expression in the objective
// is normalized: i.e., for all i != j, terms
// c(i,j)*x[i]*x[j] + c(j,i)*x[j]*x[i] are normalized as
// (c(i,j) + c(j,i)) * x[i]*x[j], or
// (c(i,j) + c(j,i)) * x[j]*x[i].
// Therefore you can only modify one of the terms
// x[i]*x[j] or x[j]*x[i].
// If you modify both x[i]*x[j] and x[j]*x[i], then
// the second modification will overwrite the first one.
for (int i = 0; i < ncols; ++i)
{
model.SetQuadCoef(obj, x[i], x[i], i * i);
for (int j = 0; j < i; ++j)
{
model.SetQuadCoef(obj, x[i], x[j], -2.0 * (i * j));
}
}
// Print out the objective function
PrintObjective(obj);
}
public static void Main(string[] args)
{
// Check length of command line
if (args.Length != 2)
{
Usage();
System.Environment.Exit(-1);
}
// Pick up VMC from command line.
string vmconfig = args[0];
// Solve the model.
Cplex cplex = null;
try {
// Create CPLEX solver and load model.
cplex = new Cplex();
cplex.ImportModel(args[1]);
// Load the virtual machine configuration.
// This will force Solve() to use distributed parallel MIP.
cplex.ReadVMConfig(vmconfig);
// Install logging info callback.
IEnumerator e = cplex.GetLPMatrixEnumerator();
e.MoveNext();
ILPMatrix lp = (ILPMatrix)e.Current;
IObjective obj = cplex.GetObjective();
double lastObjVal =
(obj.Sense == ObjectiveSense.Minimize) ?
System.Double.MaxValue : -System.Double.MaxValue;
cplex.Use(new LogCallback(lp.NumVars, -100000, lastObjVal,
cplex.GetCplexTime(), cplex.GetDetTime()));
// Turn off CPLEX logging
cplex.SetParam(Cplex.Param.MIP.Display, 0);
// Solve the model and print some solution information.
if (cplex.Solve())
{
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
}
else
{
System.Console.WriteLine("No solution available");
}
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught '" + e + "' caught");
}
finally {
if (cplex != null)
{
cplex.End();
}
}
}
public static void Main(string[] args)
{
try {
Cplex cplex = new Cplex();
ILPMatrix lp = PopulateByRow(cplex);
// turn off presolve to prevent it from completely solving the model
// before entering the actual LP optimizer
cplex.SetParam(Cplex.Param.Preprocessing.Presolve, false);
// turn off logging
cplex.SetOut(null);
// create and instruct cplex to use callback
cplex.Use(new MyCallback());
if (cplex.Solve())
{
double[] x = cplex.GetValues(lp);
double[] dj = cplex.GetReducedCosts(lp);
double[] pi = cplex.GetDuals(lp);
double[] slack = cplex.GetSlacks(lp);
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Iterations = " + cplex.Niterations);
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
int nvars = x.Length;
for (int j = 0; j < nvars; ++j)
{
System.Console.WriteLine("Variable " + j +
": Value = " + x[j] +
" Reduced cost = " + dj[j]);
}
int ncons = slack.Length;
for (int i = 0; i < ncons; ++i)
{
System.Console.WriteLine("Constraint " + i +
": Slack = " + slack[i] +
" Pi = " + pi[i]);
}
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception '" + e + "' caught");
}
}
public void setProb(Problem prob)
{
if (prob is ProblemCPLEX)
{
this.cplex = ((ProblemCPLEX)prob).cplex;
this.ilpMatrix = ((ProblemCPLEX)prob).ilpMatrix;
this.objCoef = ((ProblemCPLEX)prob).objCoef;
}
else
{
this.cplex = ((ProblemCPLEXUndirected)prob).cplex;
this.ilpMatrix = ((ProblemCPLEXUndirected)prob).ilpMatrix;
this.objCoef = ((ProblemCPLEXUndirected)prob).objCoef;
}
}
public static void Main(string[] args)
{
if (args.Length != 1)
{
System.Console.WriteLine("Usage: AdMIPex1 filename");
System.Console.WriteLine(" where filename is a file with extension ");
System.Console.WriteLine(" MPS, SAV, or LP (lower case is allowed)");
System.Console.WriteLine(" Exiting...");
System.Environment.Exit(-1);
}
try {
Cplex cplex = new Cplex();
cplex.ImportModel(args[0]);
if (cplex.NSOS1 > 0)
{
ISOS1[] sos1 = new ISOS1[cplex.NSOS1];
int i = 0;
for (IEnumerator sosenum = cplex.GetSOS1Enumerator();
sosenum.MoveNext(); ++i)
{
sos1[i] = (ISOS1)sosenum.Current;
}
cplex.Use(new SOSbranch(sos1));
System.Console.WriteLine("using SOS branch callback for " +
sos1.Length + " SOS1s");
}
cplex.SetParam(Cplex.Param.MIP.Strategy.Search, Cplex.MIPSearch.Traditional);
if (cplex.Solve())
{
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix matrix = (ILPMatrix)matrixEnum.Current;
double[] vals = cplex.GetValues(matrix);
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
}
cplex.End();
}
catch (ILOG.Concert.Exception exc) {
System.Console.WriteLine("Concert exception caught: " + exc);
}
}
// Creating a simple QP problem
internal static ILPMatrix CreateQPModel(IMPModeler model)
{
ILPMatrix lp = model.AddLPMatrix();
double[] lb = { 0.0, 0.0, 0.0 };
double[] ub = { 40.0, System.Double.MaxValue, System.Double.MaxValue };
INumVar[] x = model.NumVarArray(model.ColumnArray(lp, 3), lb, ub);
int nvars = x.Length;
for (int j = 0; j < nvars; ++j)
{
x[j].Name = "x" + j;
}
// - x0 + x1 + x2 <= 20
// x0 - 3*x1 + x2 <= 30
double[] lhs = { -System.Double.MaxValue, -System.Double.MaxValue };
double[] rhs = { 20.0, 30.0 };
double[][] val = { new double[] { -1.0, 1.0, 1.0 },
new double[] { 1.0, -3.0, 1.0 } };
int[][] ind = { new int[] { 0, 1, 2 },
new int[] { 0, 1, 2 } };
lp.AddRows(lhs, rhs, ind, val);
// minimize - x0 - x1 - x2 + x0*x0 + x1*x1 + x0*x1 + x1*x0
ILQNumExpr objExpr = model.LqNumExpr();
for (int i = 0; i < nvars; ++i)
{
objExpr.AddTerm(-1.0, x[i]);
for (int j = 0; j < nvars; ++j)
{
objExpr.AddTerm(1.0, x[i], x[j]);
}
}
IObjective obj = model.Minimize(objExpr);
model.Add(obj);
// Print out the objective function
PrintObjective(obj);
return(lp);
}
public static void Main(string[] args)
{
if (args.Length != 1)
{
System.Console.WriteLine("Usage: AdMIPex2 filename");
System.Console.WriteLine(" where filename is a file with extension ");
System.Console.WriteLine(" MPS, SAV, or LP (lower case is allowed)");
System.Console.WriteLine(" Exiting...");
System.Environment.Exit(-1);
}
try {
Cplex cplex = new Cplex();
cplex.ImportModel(args[0]);
// Check model is all binary except for objective constant variable
if (cplex.NbinVars < cplex.Ncols - 1)
{
System.Console.WriteLine(
"Problem contains non-binary variables, exiting.");
System.Environment.Exit(-1);
}
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
cplex.Use(new RoundDown(lp.NumVars));
cplex.SetParam(Cplex.Param.MIP.Strategy.Search, Cplex.MIPSearch.Traditional);
if (cplex.Solve())
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught: " + e);
}
}
public static void Main(string[] args)
{
try {
Cplex cplex = new Cplex();
ILPMatrix lp = PopulateByRow(cplex);
if (cplex.Solve())
{
double[] x = cplex.GetValues(lp);
double[] dj = cplex.GetReducedCosts(lp);
double[] pi = cplex.GetDuals(lp);
double[] slack = cplex.GetSlacks(lp);
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
int nvars = x.Length;
for (int j = 0; j < nvars; ++j)
{
System.Console.WriteLine("Variable " + j +
": Value = " + x[j] +
" Reduced cost = " + dj[j]);
}
int ncons = slack.Length;
for (int i = 0; i < ncons; ++i)
{
System.Console.WriteLine("Constraint " + i +
": Slack = " + slack[i] +
" Pi = " + pi[i]);
}
cplex.ExportModel("qpex1.lp");
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception '" + e + "' caught");
}
}
public static void Main(string[] args)
{
try {
Cplex cplex = new Cplex();
string filename = "../../../../examples/data/noswot.mps";
if (args.Length > 0)
{
filename = args[0];
if (filename.IndexOf("noswot") < 0)
{
System.Console.WriteLine("Error: noswot model is required.");
return;
}
}
cplex.ImportModel(filename);
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
// Use AddUserCuts when the added constraints strengthen the
// formulation. Use AddLazyConstraints when the added constraints
// remove part of the feasible region. Use AddCuts when you are
// not certain.
cplex.AddUserCuts(MakeCuts(cplex, lp));
cplex.SetParam(Cplex.Param.MIP.Interval, 1000);
if (cplex.Solve())
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught: " + e);
}
}
internal static ILPMatrix PopulateByRow(IMPModeler model)
{
ILPMatrix lp = model.AddLPMatrix();
double[] lb = { 0.0, 0.0, 0.0 };
double[] ub = { 40.0, System.Double.MaxValue, System.Double.MaxValue };
INumVar[] x = model.NumVarArray(model.ColumnArray(lp, 3), lb, ub);
double[] lhs = { -System.Double.MaxValue, -System.Double.MaxValue };
double[] rhs = { 20.0, 30.0 };
double[][] val = { new double[] { -1.0, 1.0, 1.0 },
new double[] { 1.0, -3.0, 1.0 } };
int[][] ind = { new int[] { 0, 1, 2 },
new int[] { 0, 1, 2 } };
lp.AddRows(lhs, rhs, ind, val);
double[] objvals = { 1.0, 2.0, 3.0 };
model.AddMaximize(model.ScalProd(x, objvals));
return(lp);
}
// Solve the current model and print results
internal static void SolveAndPrint(Cplex cplex, string msg)
{
System.Console.WriteLine(msg);
if (cplex.Solve())
{
System.Console.WriteLine();
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
double[] x = cplex.GetValues(lp);
int nvars = x.Length;
for (int j = 0; j < nvars; ++j)
{
System.Console.WriteLine("Variable " + j + ": Value = " + x[j]);
}
}
System.Console.WriteLine();
}
public static void Main(string[] args)
{
if (args.Length != 1)
{
Usage();
return;
}
try {
Cplex cplex = new Cplex();
cplex.ImportModel(args[0]);
if (cplex.Solve())
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
// access ILPMatrix object that has been read from file in order to
// access variables which are the columns of the lp. Method
// importModel guarantees to the model into exactly on ILPMatrix
// object which is why there are no test or iterations needed in the
// following line of code.
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
double[] x = cplex.GetValues(lp);
for (int j = 0; j < x.Length; ++j)
{
System.Console.WriteLine("Variable " + j + ": Value = " + x[j]);
}
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught: " + e);
}
}
public static void Main(string[] args)
{
try {
Cplex cplex = new Cplex();
cplex.ImportModel(args[0]);
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
IConversion relax = cplex.Conversion(lp.NumVars,
NumVarType.Float);
cplex.Add(relax);
cplex.Solve();
System.Console.WriteLine("Relaxed solution status = " + cplex.GetStatus());
System.Console.WriteLine("Relaxed solution value = " + cplex.ObjValue);
double[] vals = cplex.GetValues(lp.NumVars);
cplex.Use(new Solve(lp.NumVars, vals));
cplex.Delete(relax);
cplex.SetParam(Cplex.Param.MIP.Strategy.Search, Cplex.MIPSearch.Traditional);
if (cplex.Solve())
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught: " + e);
}
}
public static void Main(string[] args)
{
try {
Cplex cplex = new Cplex();
string filename = "../../../../examples/data/noswot.mps";
if (args.Length > 0)
{
filename = args[0];
if (filename.IndexOf("noswot") < 0)
{
System.Console.WriteLine("Error: noswot model is required.");
return;
}
}
cplex.ImportModel(filename);
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
cplex.Use(new Callback(MakeCuts(cplex, lp)));
cplex.SetParam(Cplex.Param.MIP.Interval, 1000);
cplex.SetParam(Cplex.Param.MIP.Strategy.Search, Cplex.MIPSearch.Traditional);
if (cplex.Solve())
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught: " + e);
}
}
internal static IRange[] MakeCuts(IModeler m, ILPMatrix lp)
{
INumVar x11 = null, x12 = null, x13 = null, x14 = null, x15 = null;
INumVar x21 = null, x22 = null, x23 = null, x24 = null, x25 = null;
INumVar x31 = null, x32 = null, x33 = null, x34 = null, x35 = null;
INumVar x41 = null, x42 = null, x43 = null, x44 = null, x45 = null;
INumVar x51 = null, x52 = null, x53 = null, x54 = null, x55 = null;
INumVar w11 = null, w12 = null, w13 = null, w14 = null, w15 = null;
INumVar w21 = null, w22 = null, w23 = null, w24 = null, w25 = null;
INumVar w31 = null, w32 = null, w33 = null, w34 = null, w35 = null;
INumVar w41 = null, w42 = null, w43 = null, w44 = null, w45 = null;
INumVar w51 = null, w52 = null, w53 = null, w54 = null, w55 = null;
INumVar[] vars = lp.NumVars;
int num = vars.Length;
for (int i = 0; i < num; ++i)
{
if (vars[i].Name.Equals("X11"))
{
x11 = vars[i];
}
else if (vars[i].Name.Equals("X12"))
{
x12 = vars[i];
}
else if (vars[i].Name.Equals("X13"))
{
x13 = vars[i];
}
else if (vars[i].Name.Equals("X14"))
{
x14 = vars[i];
}
else if (vars[i].Name.Equals("X15"))
{
x15 = vars[i];
}
else if (vars[i].Name.Equals("X21"))
{
x21 = vars[i];
}
else if (vars[i].Name.Equals("X22"))
{
x22 = vars[i];
}
else if (vars[i].Name.Equals("X23"))
{
x23 = vars[i];
}
else if (vars[i].Name.Equals("X24"))
{
x24 = vars[i];
}
else if (vars[i].Name.Equals("X25"))
{
x25 = vars[i];
}
else if (vars[i].Name.Equals("X31"))
{
x31 = vars[i];
}
else if (vars[i].Name.Equals("X32"))
{
x32 = vars[i];
}
else if (vars[i].Name.Equals("X33"))
{
x33 = vars[i];
}
else if (vars[i].Name.Equals("X34"))
{
x34 = vars[i];
}
else if (vars[i].Name.Equals("X35"))
{
x35 = vars[i];
}
else if (vars[i].Name.Equals("X41"))
{
x41 = vars[i];
}
else if (vars[i].Name.Equals("X42"))
{
x42 = vars[i];
}
else if (vars[i].Name.Equals("X43"))
{
x43 = vars[i];
}
else if (vars[i].Name.Equals("X44"))
{
x44 = vars[i];
}
else if (vars[i].Name.Equals("X45"))
{
x45 = vars[i];
}
else if (vars[i].Name.Equals("X51"))
{
x51 = vars[i];
}
else if (vars[i].Name.Equals("X52"))
{
x52 = vars[i];
}
else if (vars[i].Name.Equals("X53"))
{
x53 = vars[i];
}
else if (vars[i].Name.Equals("X54"))
{
x54 = vars[i];
}
else if (vars[i].Name.Equals("X55"))
{
x55 = vars[i];
}
else if (vars[i].Name.Equals("W11"))
{
w11 = vars[i];
}
else if (vars[i].Name.Equals("W12"))
{
w12 = vars[i];
}
else if (vars[i].Name.Equals("W13"))
{
w13 = vars[i];
}
else if (vars[i].Name.Equals("W14"))
{
w14 = vars[i];
}
else if (vars[i].Name.Equals("W15"))
{
w15 = vars[i];
}
else if (vars[i].Name.Equals("W21"))
{
w21 = vars[i];
}
else if (vars[i].Name.Equals("W22"))
{
w22 = vars[i];
}
else if (vars[i].Name.Equals("W23"))
{
w23 = vars[i];
}
else if (vars[i].Name.Equals("W24"))
{
w24 = vars[i];
}
else if (vars[i].Name.Equals("W25"))
{
w25 = vars[i];
}
else if (vars[i].Name.Equals("W31"))
{
w31 = vars[i];
}
else if (vars[i].Name.Equals("W32"))
{
w32 = vars[i];
}
else if (vars[i].Name.Equals("W33"))
{
w33 = vars[i];
}
else if (vars[i].Name.Equals("W34"))
{
w34 = vars[i];
}
else if (vars[i].Name.Equals("W35"))
{
w35 = vars[i];
}
else if (vars[i].Name.Equals("W41"))
{
w41 = vars[i];
}
else if (vars[i].Name.Equals("W42"))
{
w42 = vars[i];
}
else if (vars[i].Name.Equals("W43"))
{
w43 = vars[i];
}
else if (vars[i].Name.Equals("W44"))
{
w44 = vars[i];
}
else if (vars[i].Name.Equals("W45"))
{
w45 = vars[i];
}
else if (vars[i].Name.Equals("W51"))
{
w51 = vars[i];
}
else if (vars[i].Name.Equals("W52"))
{
w52 = vars[i];
}
else if (vars[i].Name.Equals("W53"))
{
w53 = vars[i];
}
else if (vars[i].Name.Equals("W54"))
{
w54 = vars[i];
}
else if (vars[i].Name.Equals("W55"))
{
w55 = vars[i];
}
}
IRange[] cut = new IRange[8];
cut[0] = m.Le(m.Diff(x21, x22), 0.0);
cut[1] = m.Le(m.Diff(x22, x23), 0.0);
cut[2] = m.Le(m.Diff(x23, x24), 0.0);
cut[3] = m.Le(m.Sum(m.Sum(m.Prod(2.08, x11),
m.Prod(2.98, x21),
m.Prod(3.47, x31),
m.Prod(2.24, x41),
m.Prod(2.08, x51)),
m.Sum(m.Prod(0.25, w11),
m.Prod(0.25, w21),
m.Prod(0.25, w31),
m.Prod(0.25, w41),
m.Prod(0.25, w51))), 20.25);
cut[4] = m.Le(m.Sum(m.Sum(m.Prod(2.08, x12),
m.Prod(2.98, x22),
m.Prod(3.47, x32),
m.Prod(2.24, x42),
m.Prod(2.08, x52)),
m.Sum(m.Prod(0.25, w12),
m.Prod(0.25, w22),
m.Prod(0.25, w32),
m.Prod(0.25, w42),
m.Prod(0.25, w52))), 20.25);
cut[5] = m.Le(m.Sum(m.Sum(m.Prod(2.08, x13),
m.Prod(2.98, x23),
m.Prod(3.47, x33),
m.Prod(2.24, x43),
m.Prod(2.08, x53)),
m.Sum(m.Prod(0.25, w13),
m.Prod(0.25, w23),
m.Prod(0.25, w33),
m.Prod(0.25, w43),
m.Prod(0.25, w53))), 20.25);
cut[6] = m.Le(m.Sum(m.Sum(m.Prod(2.08, x14),
m.Prod(2.98, x24),
m.Prod(3.47, x34),
m.Prod(2.24, x44),
m.Prod(2.08, x54)),
m.Sum(m.Prod(0.25, w14),
m.Prod(0.25, w24),
m.Prod(0.25, w34),
m.Prod(0.25, w44),
m.Prod(0.25, w54))), 20.25);
cut[7] = m.Le(m.Sum(m.Sum(m.Prod(2.08, x15),
m.Prod(2.98, x25),
m.Prod(3.47, x35),
m.Prod(2.24, x45),
m.Prod(2.08, x55)),
m.Sum(m.Prod(0.25, w15),
m.Prod(0.25, w25),
m.Prod(0.25, w35),
m.Prod(0.25, w45),
m.Prod(0.25, w55))), 16.25);
return(cut);
}
public static void Main(string[] args)
{
try {
int ncols = 12;
Cplex cplex = new Cplex();
ILPMatrix lp = cplex.AddLPMatrix();
// add empty corresponding to new variables columns to lp
INumVar[] x = cplex.NumVarArray(cplex.ColumnArray(lp, ncols), 0, 50);
// add rows to lp
double[] d = { -1.0, 4.0, 1.0, 1.0, -2.0, -2.0, -1.0 };
double[][] valH = { new double[] { -1.0, -1.0, -1.0 },
new double[] { 1.0, 1.0, 1.0 },
new double[] { 1.0, 1.0,1.0, 1.0 },
new double[] { 1.0, 1.0, 1.0 },
new double[] { -1.0, -1.0,-1.0, 1.0 },
new double[] { -1.0, -1.0, 1.0 },
new double[] { -1.0, -1.0,-1.0, -1.0 } };
int[][] indH = { new int[] { 7, 8, 9 },
new int[] { 0, 5, 7 },
new int[] { 1, 3,6, 8 },
new int[] { 2, 4, 9 },
new int[] { 5, 6,10, 11 },
new int[] { 3, 4, 10 },
new int[] { 0, 1,2, 11 } };
lp.AddRows(d, d, indH, valH);
// add the objective function
double[] objvals = { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
1.0, 0.0, 0.0, 0.0, 2.0, 2.0 };
cplex.AddMinimize(cplex.ScalProd(x, objvals));
// Solve initial problem with the network optimizer
cplex.SetParam(Cplex.Param.RootAlgorithm, Cplex.Algorithm.Network);
cplex.Solve();
System.Console.WriteLine("After network optimization, objective is "
+ cplex.ObjValue);
// add rows from matrix A to lp
double[] b = { 2.0, 3.0 };
double[][] valA = { new double[] { 2.0, 5.0 },
new double[] { 1.0,1.0, 1.0 } };
int[][] indA = { new int[] { 10, 11 },
new int[] { 0,2, 5 } };
lp.AddRows(b, b, indA, valA);
// Because the problem is dual feasible with the rows added, using
// the dual simplex method is indicated.
cplex.SetParam(Cplex.Param.RootAlgorithm, Cplex.Algorithm.Dual);
if (cplex.Solve())
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
double[] sol = cplex.GetValues(lp);
for (int j = 0; j < ncols; ++j)
{
System.Console.WriteLine("Variable " + j + ": Value = " + sol[j]);
}
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception '" + e + "' caught");
}
}
public static void Main(string[] args)
{
if (args.Length != 2)
{
Usage();
return;
}
try {
// Create the modeler/solver object
Cplex cplex = new Cplex();
// Evaluate command line option and set optimization method accordingly.
switch (args[1].ToCharArray()[0])
{
case 'o': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Auto);
break;
case 'p': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Primal);
break;
case 'd': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Dual);
break;
case 'h': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Barrier);
break;
case 'b': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Barrier);
cplex.SetParam(Cplex.Param.Barrier.Crossover,
Cplex.Algorithm.None);
break;
case 'n': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Network);
break;
case 's': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Sifting);
break;
case 'c': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Concurrent);
break;
default: Usage();
return;
}
// Read model from file with name args[0] into cplex optimizer object
cplex.ImportModel(args[0]);
// Solve the model and display the solution if one was found
if (cplex.Solve())
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
// Access the ILPMatrix object that has been read from a file in
// order to access variables which are the columns of the LP. The
// method importModel() guarantees that exactly one ILPMatrix
// object will exist, which is why no tests or enumerators are
// needed in the following line of code.
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
double[] x = cplex.GetValues(lp);
for (int j = 0; j < x.Length; ++j)
{
System.Console.WriteLine("Variable " + j + ": Value = " + x[j]);
}
try { // basis may not exist
Cplex.BasisStatus[] cstat =
cplex.GetBasisStatuses(lp.NumVars);
for (int j = 0; j < x.Length; ++j)
{
System.Console.WriteLine("Variable " + j + ": Basis Status = " + cstat[j]);
}
}
catch (System.Exception) {
}
System.Console.WriteLine("Maximum bound violation = " +
cplex.GetQuality(Cplex.QualityType.MaxPrimalInfeas));
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught: " + e);
}
}
public static void Main(string[] args)
{
if (args.Length != 1)
{
Usage();
return;
}
try {
Cplex cplex = new Cplex();
cplex.ImportModel(args[0]);
/* Set the solution pool relative gap parameter to obtain solutions
* of objective value within 10% of the optimal */
cplex.SetParam(Cplex.Param.MIP.Pool.RelGap, 0.1);
if (cplex.Populate())
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Incumbent objective value = " +
cplex.ObjValue);
// access ILPMatrix object that has been read from file in order to
// access variables which are the columns of the lp. Method
// importModel guarantees to the model into exactly on ILPMatrix
// object which is why there are no test or iterations needed in the
// following line of code.
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
double[] incx = cplex.GetValues(lp);
for (int j = 0; j < incx.Length; j++)
{
System.Console.WriteLine("Variable " + j + ": Value = " + incx[j]);
}
System.Console.WriteLine();
/* Get the number of solutions in the solution pool */
int numsol = cplex.SolnPoolNsolns;
System.Console.WriteLine("The solution pool contains " + numsol +
" solutions.");
/* Some solutions are deleted from the pool because of the
* solution pool relative gap parameter */
int numsolreplaced = cplex.SolnPoolNreplaced;
System.Console.WriteLine(numsolreplaced +
" solutions were removed due to the " +
"solution pool relative gap parameter.");
System.Console.WriteLine("In total, " + (numsol + numsolreplaced) +
" solutions were generated.");
/* Get the average objective value of solutions in the
* solution pool */
System.Console.WriteLine(
"The average objective value of the solutions is " +
cplex.SolnPoolMeanObjValue + ".");
System.Console.WriteLine();
/* Write out the objective value of each solution and its
* difference to the incumbent */
for (int i = 0; i < numsol; i++)
{
double[] x = cplex.GetValues(lp, i);
/* Compute the number of variables that differ in the
* solution and in the incumbent */
int numdiff = 0;
for (int j = 0; j < x.Length; ++j)
{
if (System.Math.Abs(x[j] - incx[j]) > EPSZERO)
{
numdiff++;
}
}
System.Console.WriteLine("Solution " + i +
" with objective " +
cplex.GetObjValue(i) +
" differs in " +
numdiff + " of " + x.Length +
" variables.");
}
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught: " + e);
}
}
public static void Main(string[] args)
{
if (args.Length != 2)
{
Usage();
return;
}
try {
// Create the modeler/solver object
Cplex cplex = new Cplex();
// Evaluate command line option and set optimization method accordingly.
switch (args[1].ToCharArray()[0])
{
case 'o': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Auto);
break;
case 'p': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Primal);
break;
case 'd': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Dual);
break;
case 'h': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Barrier);
break;
case 'b': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Barrier);
cplex.SetParam(Cplex.Param.Barrier.Crossover,
Cplex.Algorithm.None);
break;
case 'n': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Network);
break;
case 's': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Sifting);
break;
case 'c': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Concurrent);
break;
default: Usage();
return;
}
// Read model from file with name args[0] into cplex optimizer object
cplex.ImportModel(args[0]);
// Solve the model and display the solution if one was found
if (cplex.Solve())
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
// Access the ILPMatrix object that has been read from a file in
// order to access variables which are the columns of the LP. The
// method importModel() guarantees that exactly one ILPMatrix
// object will exist, which is why no tests or enumerators are
// needed in the following line of code.
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
INumVar[] vars = lp.NumVars;
double[] vals = cplex.GetValues(vars);
// Basis information is not available for barrier without crossover.
// Thus we include the query in a try statement and print the solution
// without barrier information in case we get an exception.
try {
Cplex.BasisStatus[] bStat = cplex.GetBasisStatuses(vars);
for (int i = 0; i < vals.Length; i++)
{
System.Console.WriteLine("Variable " + vars[i].Name +
" has vals " + vals[i] +
" and status " + bStat[i]);
}
}
catch (ILOG.Concert.Exception) {
for (int i = 0; i < vals.Length; i++)
{
System.Console.WriteLine("Variable " + vars[i].Name +
" has vals " + vals[i]);
}
}
}
cplex.End();
}
catch (ILOG.Concert.Exception exc) {
System.Console.WriteLine("Concert exception '" + exc + "' caught");
}
}
internal static void SolveAndDisplay(Cplex cplex, ILPMatrix lp)
{
if ( cplex.Solve() ) {
double[] x = cplex.GetValues(lp);
double[] dj = cplex.GetReducedCosts(lp);
double[] pi = cplex.GetDuals(lp);
double[] slack = cplex.GetSlacks(lp);
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.GetObjValue());
int nvars = x.Length;
for (int j = 0; j < nvars; ++j) {
System.Console.WriteLine("Variable " + j +": Value = " + x[j] +" Reduced cost = " + dj[j]);
}
int ncons = slack.Length;
for (int i = 0; i < ncons; ++i) {
System.Console.WriteLine("Constraint " + i +": Slack = " + slack[i] +" Pi = " + pi[i]);
}
}
}
public static void Main(string[] args)
{
if (args.Length != 2)
{
Usage();
return;
}
try {
bool useLoggingCallback = false;
bool useTimeLimitCallback = false;
bool useAborter = false;
Cplex.Aborter myAborter;
switch (args[1].ToCharArray()[0])
{
case 't':
useTimeLimitCallback = true;
break;
case 'l':
useLoggingCallback = true;
break;
case 'a':
useAborter = true;
break;
default:
Usage();
return;
}
Cplex cplex = new Cplex();
cplex.ImportModel(args[0]);
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
IObjective obj = cplex.GetObjective();
// Set an overall node limit in case callback conditions
// are not met.
cplex.SetParam(Cplex.Param.MIP.Limits.Nodes, 5000);
if (useLoggingCallback)
{
double lastObjVal =
(obj.Sense == ObjectiveSense.Minimize) ?
System.Double.MaxValue : -System.Double.MaxValue;
cplex.Use(new LogCallback(lp.NumVars, -100000, lastObjVal));
// Turn off CPLEX logging
cplex.SetParam(Cplex.Param.MIP.Display, 0);
}
else if (useTimeLimitCallback)
{
cplex.Use(new TimeLimitCallback(cplex, false, cplex.CplexTime,
1.0, 10.0));
}
else if (useAborter)
{
myAborter = new Cplex.Aborter();
cplex.Use(myAborter);
// Typically, you would pass the Aborter object to
// another thread or pass it to an interrupt handler,
// and monitor for some event to occur. When it does,
// call the Aborter's abort method.
//
// To illustrate its use without creating a thread or
// an interrupt handler, abort immediately by calling
// abort before the solve.
//
myAborter.Abort();
}
cplex.Solve();
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Cplex status = " + cplex.GetCplexStatus());
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught: " + e);
}
}
public static IRange[] MakeCuts(IModeler m, ILPMatrix lp) {
INumVar x11 = null, x12 = null, x13 = null, x14 = null, x15 = null;
INumVar x21 = null, x22 = null, x23 = null, x24 = null, x25 = null;
INumVar x31 = null, x32 = null, x33 = null, x34 = null, x35 = null;
INumVar x41 = null, x42 = null, x43 = null, x44 = null, x45 = null;
INumVar x51 = null, x52 = null, x53 = null, x54 = null, x55 = null;
INumVar w11 = null, w12 = null, w13 = null, w14 = null, w15 = null;
INumVar w21 = null, w22 = null, w23 = null, w24 = null, w25 = null;
INumVar w31 = null, w32 = null, w33 = null, w34 = null, w35 = null;
INumVar w41 = null, w42 = null, w43 = null, w44 = null, w45 = null;
INumVar w51 = null, w52 = null, w53 = null, w54 = null, w55 = null;
INumVar[] vars = lp.NumVars;
int num = vars.Length;
for (int i = 0; i < num; ++i) {
if ( vars[i].Name.Equals("X11") ) x11 = vars[i];
else if ( vars[i].Name.Equals("X12") ) x12 = vars[i];
else if ( vars[i].Name.Equals("X13") ) x13 = vars[i];
else if ( vars[i].Name.Equals("X14") ) x14 = vars[i];
else if ( vars[i].Name.Equals("X15") ) x15 = vars[i];
else if ( vars[i].Name.Equals("X21") ) x21 = vars[i];
else if ( vars[i].Name.Equals("X22") ) x22 = vars[i];
else if ( vars[i].Name.Equals("X23") ) x23 = vars[i];
else if ( vars[i].Name.Equals("X24") ) x24 = vars[i];
else if ( vars[i].Name.Equals("X25") ) x25 = vars[i];
else if ( vars[i].Name.Equals("X31") ) x31 = vars[i];
else if ( vars[i].Name.Equals("X32") ) x32 = vars[i];
else if ( vars[i].Name.Equals("X33") ) x33 = vars[i];
else if ( vars[i].Name.Equals("X34") ) x34 = vars[i];
else if ( vars[i].Name.Equals("X35") ) x35 = vars[i];
else if ( vars[i].Name.Equals("X41") ) x41 = vars[i];
else if ( vars[i].Name.Equals("X42") ) x42 = vars[i];
else if ( vars[i].Name.Equals("X43") ) x43 = vars[i];
else if ( vars[i].Name.Equals("X44") ) x44 = vars[i];
else if ( vars[i].Name.Equals("X45") ) x45 = vars[i];
else if ( vars[i].Name.Equals("X51") ) x51 = vars[i];
else if ( vars[i].Name.Equals("X52") ) x52 = vars[i];
else if ( vars[i].Name.Equals("X53") ) x53 = vars[i];
else if ( vars[i].Name.Equals("X54") ) x54 = vars[i];
else if ( vars[i].Name.Equals("X55") ) x55 = vars[i];
else if ( vars[i].Name.Equals("W11") ) w11 = vars[i];
else if ( vars[i].Name.Equals("W12") ) w12 = vars[i];
else if ( vars[i].Name.Equals("W13") ) w13 = vars[i];
else if ( vars[i].Name.Equals("W14") ) w14 = vars[i];
else if ( vars[i].Name.Equals("W15") ) w15 = vars[i];
else if ( vars[i].Name.Equals("W21") ) w21 = vars[i];
else if ( vars[i].Name.Equals("W22") ) w22 = vars[i];
else if ( vars[i].Name.Equals("W23") ) w23 = vars[i];
else if ( vars[i].Name.Equals("W24") ) w24 = vars[i];
else if ( vars[i].Name.Equals("W25") ) w25 = vars[i];
else if ( vars[i].Name.Equals("W31") ) w31 = vars[i];
else if ( vars[i].Name.Equals("W32") ) w32 = vars[i];
else if ( vars[i].Name.Equals("W33") ) w33 = vars[i];
else if ( vars[i].Name.Equals("W34") ) w34 = vars[i];
else if ( vars[i].Name.Equals("W35") ) w35 = vars[i];
else if ( vars[i].Name.Equals("W41") ) w41 = vars[i];
else if ( vars[i].Name.Equals("W42") ) w42 = vars[i];
else if ( vars[i].Name.Equals("W43") ) w43 = vars[i];
else if ( vars[i].Name.Equals("W44") ) w44 = vars[i];
else if ( vars[i].Name.Equals("W45") ) w45 = vars[i];
else if ( vars[i].Name.Equals("W51") ) w51 = vars[i];
else if ( vars[i].Name.Equals("W52") ) w52 = vars[i];
else if ( vars[i].Name.Equals("W53") ) w53 = vars[i];
else if ( vars[i].Name.Equals("W54") ) w54 = vars[i];
else if ( vars[i].Name.Equals("W55") ) w55 = vars[i];
}
IRange[] cut = new IRange[8];
cut[0] = m.Le(m.Diff(x21, x22), 0.0);
cut[1] = m.Le(m.Diff(x22, x23), 0.0);
cut[2] = m.Le(m.Diff(x23, x24), 0.0);
cut[3] = m.Le(m.Sum(m.Sum(m.Prod(2.08, x11),
m.Prod(2.98, x21),
m.Prod(3.47, x31),
m.Prod(2.24, x41),
m.Prod(2.08, x51)),
m.Sum(m.Prod(0.25, w11),
m.Prod(0.25, w21),
m.Prod(0.25, w31),
m.Prod(0.25, w41),
m.Prod(0.25, w51))), 20.25);
cut[4] = m.Le(m.Sum(m.Sum(m.Prod(2.08, x12),
m.Prod(2.98, x22),
m.Prod(3.47, x32),
m.Prod(2.24, x42),
m.Prod(2.08, x52)),
m.Sum(m.Prod(0.25, w12),
m.Prod(0.25, w22),
m.Prod(0.25, w32),
m.Prod(0.25, w42),
m.Prod(0.25, w52))), 20.25);
cut[5] = m.Le(m.Sum(m.Sum(m.Prod(2.08, x13),
m.Prod(2.98, x23),
m.Prod(3.47, x33),
m.Prod(2.24, x43),
m.Prod(2.08, x53)),
m.Sum(m.Prod(0.25, w13),
m.Prod(0.25, w23),
m.Prod(0.25, w33),
m.Prod(0.25, w43),
m.Prod(0.25, w53))), 20.25);
cut[6] = m.Le(m.Sum(m.Sum(m.Prod(2.08, x14),
m.Prod(2.98, x24),
m.Prod(3.47, x34),
m.Prod(2.24, x44),
m.Prod(2.08, x54)),
m.Sum(m.Prod(0.25, w14),
m.Prod(0.25, w24),
m.Prod(0.25, w34),
m.Prod(0.25, w44),
m.Prod(0.25, w54))), 20.25);
cut[7] = m.Le(m.Sum(m.Sum(m.Prod(2.08, x15),
m.Prod(2.98, x25),
m.Prod(3.47, x35),
m.Prod(2.24, x45),
m.Prod(2.08, x55)),
m.Sum(m.Prod(0.25, w15),
m.Prod(0.25, w25),
m.Prod(0.25, w35),
m.Prod(0.25, w45),
m.Prod(0.25, w55))), 16.25);
return cut;
}
public static void Main(string[] args)
{
if (args.Length != 2)
{
Usage();
return;
}
try {
Cplex cplex = new Cplex();
// Evaluate command line option and set optimization method accordingly.
switch (args[1].ToCharArray()[0])
{
case 'o': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Auto);
break;
case 'p': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Primal);
break;
case 'd': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Dual);
break;
case 'b': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Barrier);
cplex.SetParam(Cplex.Param.Barrier.Crossover,
Cplex.Algorithm.None);
break;
case 'n': cplex.SetParam(Cplex.Param.RootAlgorithm,
Cplex.Algorithm.Network);
break;
default: Usage();
return;
}
cplex.ImportModel(args[0]);
if (cplex.Solve())
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
double[] x = cplex.GetValues(lp);
for (int j = 0; j < x.Length; ++j)
{
System.Console.WriteLine("Variable " + j + ": Value = " + x[j]);
}
}
cplex.End();
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught: " + e);
}
}
//A quadratic interger program for graph matching,
//When tuned with the right similarity function it can represent the GED problem.
// See Pattern Reocgnition Paper paper On the unification of graph matching and graph edit distance paper.
//The directed version has not been tested yet
public override void QAPGMGED()
{
//some important variables
int nbNode1 = graph1.ListNodes.Count;
int nbNode2 = graph2.ListNodes.Count;
int nbvar = nbNode1 * nbNode2; // number of variables
int nbcontraintes = nbNode1 + nbNode2; // number of constraints
Graphs.Label nodeepslabel;
//Adjacency matrices
MatrixLibrary.Matrix adj1 = graph1.calculateAdjacencyMatrix();
MatrixLibrary.Matrix adj2 = graph2.calculateAdjacencyMatrix();
//Similarity matrix
Double[,] S = new Double[nbvar, nbvar];
//Creation of the Similarity matrix
//4 for loops integrated
int countrow = -1;
for (int i = 0; i < nbNode1; i++)
{
Node nodei = graph1.ListNodes[i];
for (int k = 0; k < nbNode2; k++)
{
Node nodek = graph2.ListNodes[k];
countrow = countrow + 1;
int countcol = -1;
for (int j = 0; j < nbNode1; j++)
{
Node nodej = graph1.ListNodes[j];
for (int l = 0; l < nbNode2; l++)
{
Node nodel = graph2.ListNodes[l];
countcol = countcol + 1;
if (i == j && k == l) // Similarity between nodes
{
Type typeLabel = nodei.Label.GetType();
object obj = Activator.CreateInstance(typeLabel);
nodeepslabel = (Graphs.Label)obj;
nodeepslabel.Id = ConstantsAC.EPS_ID;
double costsub = nodei.Label.dissimilarity(nodek.Label);
double costdel = nodei.Label.dissimilarity(nodeepslabel);
double costins = nodeepslabel.dissimilarity(nodek.Label);
double cost = costsub - costdel - costins;
cost *= -1;
S[countrow, countcol] = cost;
}
else // Similarity between edges
{
int connect1 = (int)adj1[i, j];
int connect2 = (int)adj2[k, l];
if (connect1 == 1 && connect2 == 1) // Two edges are connected
{
Edge ij = findedge(nodei, nodej);
Edge kl = findedge(nodek, nodel);
Type typeLabel = ij.Label.GetType();
object obj = Activator.CreateInstance(typeLabel);
nodeepslabel = (Graphs.Label)obj;
nodeepslabel.Id = ConstantsAC.EPS_ID;
double costsub = ij.Label.dissimilarity(kl.Label);
double costdel = ij.Label.dissimilarity(nodeepslabel);
double costins = nodeepslabel.dissimilarity(kl.Label);
double cost = costsub - costdel - costins;
cost *= -1;
//cost *= 0.5;
S[countrow, countcol] = cost;
}
}
}
}
}
}
//We compute the constant that represents the
//deletion and insertion of the nodes and edges
//deletions of the nodes of g1
double constante = 0;
for (int i = 1; i <= nbNode1; i++)
{
Type typeLabel = graph1.ListNodes[i - 1].Label.GetType();
object obj = Activator.CreateInstance(typeLabel);
nodeepslabel = (Graphs.Label)obj;
nodeepslabel.Id = ConstantsAC.EPS_ID;
constante += (graph1.ListNodes[i - 1].Label).dissimilarity(nodeepslabel);
}
//deletions of the edges of g1
for (int ij = 1; ij <= nbEdge1; ij++)
{
Type typeLabel = graph1.ListEdges[ij - 1].Label.GetType();
object obj = Activator.CreateInstance(typeLabel);
nodeepslabel = (Graphs.Label)obj;
nodeepslabel.Id = ConstantsAC.EPS_ID;
double costEdge = (graph1.ListEdges[ij - 1].Label).dissimilarity(nodeepslabel);
constante += costEdge;
}
//insertions of the nodes of g2
for (int k = 1; k <= nbNode2; k++)
{
Type typeLabel = graph2.ListNodes[k - 1].Label.GetType();
object obj = Activator.CreateInstance(typeLabel);
nodeepslabel = (Graphs.Label)obj;
nodeepslabel.Id = ConstantsAC.EPS_ID;
constante += (graph2.ListNodes[k - 1].Label).dissimilarity(nodeepslabel);
}
//insertions of the edges of g2
for (int kl = 1; kl <= nbEdge2; kl++)
{
Type typeLabel = graph2.ListEdges[kl - 1].Label.GetType();
object obj = Activator.CreateInstance(typeLabel);
nodeepslabel = (Graphs.Label)obj;
nodeepslabel.Id = ConstantsAC.EPS_ID;
double costEdge = (graph2.ListEdges[kl - 1].Label).dissimilarity(nodeepslabel);
constante += costEdge;
}
// the number of variables is the number of columns
int nbCols = nbvar;
// the number of constraints is the number of rows
int nbRows = nbcontraintes;
List <string> colNameList = new List <string>();
//We create the name of the vrariables for all couples of nodes in g1 and g2
for (int i = 0; i < nbNode1; i++)
{
for (int k = 0; k < nbNode2; k++)
{
colNameList.Add("x_" + graph1.ListNodes[i].Id + "," + graph2.ListNodes[k].Id + "");
}
}
try
{
cplex = new Cplex(); // creation du modèle CPLEX
this.ilpMatrix = cplex.AddLPMatrix(); // matrice du pb (initialisée à 0 colonnes et 0 lignes)
ColumnArray colonnes = cplex.ColumnArray(ilpMatrix, nbCols); // définition des variables-colonnes du pb
// ajout des variables-colonnes dans la matrice du pb
// y is a vector
INumVar[] y = cplex.NumVarArray(colonnes, 0, 1, NumVarType.Bool, colNameList.ToArray());
#region création fonction objectif
// CALCUL DES COEFFICIENTS
// We create the ojective function
INumExpr[] coeffs_expr = new INumExpr[nbvar * nbvar]; // vecteur des coeffs des coûts des arrêtes
int count = 0;
for (int ik = 0; ik < nbvar; ik++)
{
for (int jl = 0; jl < nbvar; jl++)
{
coeffs_expr[count] = cplex.Prod(y[ik], y[jl]);
coeffs_expr[count] = cplex.Prod(S[ik, jl], coeffs_expr[count]);
count = count + 1;
}
}
INumExpr ff = cplex.Sum(coeffs_expr);
INumExpr gg = cplex.Sum(ff, cplex.Constant(-constante));
cplex.AddMaximize(gg);
#endregion
#region définition des contraintes du pb
// We create the constraints
// The sum of x variables by rows
for (int i = 0; i < nbNode1; i++)
{
INumVar[] sommeLignes = new INumVar[nbNode2];
for (int k = 0; k < nbNode2; k++)
{
string nameVarik = "x_" + i + "," + k;
int indexik = SolverCPLEX.GetIndexByName(y, nameVarik);
sommeLignes[k] = y[indexik];
}
cplex.AddLe(cplex.Sum(sommeLignes), 1);
}
// The sum of x variables by columns
for (int k = 0; k < nbNode2; k++)
{
INumVar[] sommeLignes = new INumVar[nbNode1];
for (int i = 0; i < nbNode1; i++)
{
string nameVarik = "x_" + i + "," + k;
int indexik = SolverCPLEX.GetIndexByName(y, nameVarik);
sommeLignes[i] = y[indexik];
}
cplex.AddLe(cplex.Sum(sommeLignes), 1);
}
#endregion
}
catch (ILOG.Concert.Exception e)
{
System.Console.WriteLine("Concert exception `" + e + "` caught");
}
}
public override void IsoGraphInexactF1b()
{
this.nbRows = nbNode1 + nbEdge1 + nbNode2 + nbEdge2 + 3 * nbEdge1 * nbEdge2; //ns + ms+ng+mg+3msmg
this.nbCols = nbNode1 * nbNode2 + nbEdge1 * nbEdge2 + nbNode1 + nbEdge1 + nbNode2 + nbEdge2; //nsng+msmg+ns+ms+ng+mg
Graphs.Label nodeepslabel;
#region objectFunction
List <double> objList = new List <double>();
List <string> colNameList = new List <string>();
List <char> typeList = new List <char>();
List <Double> ubList = new List <Double>();
//the objet funcion
for (int i = 1; i <= nbNode1; i++)
{
for (int k = 1; k <= nbNode2; k++)
{
objList.Add(graph1.ListNodes[i - 1].Label.dissimilarity(graph2.ListNodes[k - 1].Label));
colNameList.Add("x_" + graph1.ListNodes[i - 1].Id + "," + graph2.ListNodes[k - 1].Id);
}
}
for (int ij = 1; ij <= nbEdge1; ij++)
{
for (int kl = 1; kl <= nbEdge2; kl++)
{
double costEdge = graph1.ListEdges[ij - 1].Label.dissimilarity(graph2.ListEdges[kl - 1].Label);
if (copyEdge)
{
objList.Add(costEdge / 2);
}
else
{
objList.Add(costEdge);
}
colNameList.Add("y_" + graph1.ListEdges[ij - 1].Id + "," + graph2.ListEdges[kl - 1].Id);
}
}
for (int i = 1; i <= nbNode1; i++)
{
Type typeLabel = graph1.ListNodes[i - 1].Label.GetType();
object obj = Activator.CreateInstance(typeLabel);
nodeepslabel = (Graphs.Label)obj;
nodeepslabel.Id = ConstantsAC.EPS_ID;
objList.Add((graph1.ListNodes[i - 1].Label).dissimilarity(nodeepslabel));
colNameList.Add("u_" + graph1.ListNodes[i - 1].Id + ",Ins_" + graph1.ListNodes[i - 1].Id);
}
for (int ij = 1; ij <= nbEdge1; ij++)
{
Type typeLabel = graph1.ListEdges[ij - 1].Label.GetType();
object obj = Activator.CreateInstance(typeLabel);
nodeepslabel = (Graphs.Label)obj;
nodeepslabel.Id = ConstantsAC.EPS_ID;
double costEdge = (graph1.ListEdges[ij - 1].Label).dissimilarity(nodeepslabel);
if (copyEdge)
{
objList.Add(costEdge / 2);
}
else
{
objList.Add(costEdge);
}
colNameList.Add("e_" + graph1.ListEdges[ij - 1].Id + ",Ins_" + graph1.ListEdges[ij - 1].Id);
}
for (int k = 1; k <= nbNode2; k++)
{
Type typeLabel = graph2.ListNodes[k - 1].Label.GetType();
object obj = Activator.CreateInstance(typeLabel);
nodeepslabel = (Graphs.Label)obj;
nodeepslabel.Id = ConstantsAC.EPS_ID;
objList.Add((graph2.ListNodes[k - 1].Label).dissimilarity(nodeepslabel));
colNameList.Add("v_Del_" + graph2.ListNodes[k - 1].Id + "," + graph2.ListNodes[k - 1].Id);
}
for (int kl = 1; kl <= nbEdge2; kl++)
{
Type typeLabel = graph2.ListEdges[kl - 1].Label.GetType();
object obj = Activator.CreateInstance(typeLabel);
nodeepslabel = (Graphs.Label)obj;
nodeepslabel.Id = ConstantsAC.EPS_ID;
double costEdge = (graph2.ListEdges[kl - 1].Label).dissimilarity(nodeepslabel);
if (copyEdge)
{
objList.Add(costEdge / 2);
}
else
{
objList.Add(costEdge);
}
colNameList.Add("f_Del_" + graph2.ListEdges[kl - 1].Id + "," + graph2.ListEdges[kl - 1].Id);
}
#endregion
try
{
cplex = new Cplex();
ilpMatrix = cplex.AddLPMatrix();
// add empty corresponding to new variables columns to ilpMatrix
INumVar[] x = cplex.NumVarArray(cplex.ColumnArray(ilpMatrix, nbCols), 0, 1, NumVarType.Bool, colNameList.ToArray());
List <Double> lbMatrixList = new List <Double>();
List <Double> ubMatrixList = new List <Double>();
Int32[][] indiceH = new Int32[nbRows][];
Double[][] valeurH = new Double[nbRows][];
List <Int32> jaList; //les indice des valeurs
List <Double> arList; //les valeurs non zeros dans la ligne
int rownum = 0;
#region construir constraintes
for (int i = 0; i < nbNode1; i++)
{
jaList = new List <int>();
arList = new List <Double>();
lbMatrixList.Add(1.0);
ubMatrixList.Add(1.0);
for (int k = 0; k < nbNode2; k++)
{
jaList.Add(i * nbNode2 + k);
arList.Add(1);
}
jaList.Add(nbNode1 * nbNode2 + nbEdge1 * nbEdge2 + i);
arList.Add(1);
indiceH[rownum] = jaList.ToArray();
valeurH[rownum] = arList.ToArray();
rownum++;
}
// equation 3
for (int ij = 0; ij < nbEdge1; ij++)
{
jaList = new List <int>();
arList = new List <Double>();
lbMatrixList.Add(1.0);
ubMatrixList.Add(1.0);
for (int kl = 0; kl < nbEdge2; kl++)
{
jaList.Add(nbNode1 * nbNode2 + ij * nbEdge2 + kl);
arList.Add(1);
}
jaList.Add(nbNode1 * nbNode2 + nbEdge1 * nbEdge2 + nbNode1 + ij);
arList.Add(1);
indiceH[rownum] = jaList.ToArray();
valeurH[rownum] = arList.ToArray();
rownum++;
}
// contraint: equation [Fb.1]-4
for (int k = 0; k < nbNode2; k++)
{
jaList = new List <int>();
arList = new List <Double>();
lbMatrixList.Add(1.0);
ubMatrixList.Add(1.0);
for (int i = 0; i < nbNode1; i++)
{
jaList.Add(i * nbNode2 + k);
arList.Add(1);
}
jaList.Add(nbNode1 * nbNode2 + nbEdge1 * nbEdge2 + nbNode1 + nbEdge1 + k);
arList.Add(1);
indiceH[rownum] = jaList.ToArray();
valeurH[rownum] = arList.ToArray();
rownum++;
}
// equation 5
for (int kl = 0; kl < nbEdge2; kl++)
{
jaList = new List <int>(); //les indice des valeurs
arList = new List <Double>(); //les valeurs non zeros dans la ligne
lbMatrixList.Add(1.0);
ubMatrixList.Add(1.0);
for (int ij = 0; ij < nbEdge1; ij++)
{
jaList.Add(nbNode1 * nbNode2 + ij * nbEdge2 + kl);
arList.Add(1);
}
jaList.Add(nbNode1 * nbNode2 + nbEdge1 * nbEdge2 + nbNode1 + nbEdge1 + nbNode2 + kl);
arList.Add(1);
indiceH[rownum] = jaList.ToArray();
valeurH[rownum] = arList.ToArray();
rownum++;
}
//equation 6 7 8
for (int ij = 0; ij < nbEdge1; ij++)
{
for (int kl = 0; kl < nbEdge2; kl++)
{
string source_i = graph1.ListEdges[ij].NodeSource.Id;
string source_k = graph2.ListEdges[kl].NodeSource.Id;
string target_i = graph1.ListEdges[ij].NodeTarget.Id;
string target_k = graph2.ListEdges[kl].NodeTarget.Id;
string nameVar = "x_" + source_i + "," + source_k;
int colInd = SolverCPLEX.GetIndexByName(x, nameVar);
if (colInd == -1)
{
throw new InvalidProgramException();
}
string nameVar2 = "x_" + target_i + "," + target_k;
int colInd2 = SolverCPLEX.GetIndexByName(x, nameVar2);
if (colInd2 == -1)
{
throw new InvalidProgramException();
}
jaList = new List <int>();
arList = new List <Double>();
lbMatrixList.Add(0.0);
ubMatrixList.Add(1.0);
jaList.Add(colInd);
arList.Add(1);
jaList.Add(nbNode1 * nbNode2 + ij * nbEdge2 + kl);
arList.Add(-1);
indiceH[rownum] = jaList.ToArray();
valeurH[rownum] = arList.ToArray();
rownum++;
////////////////////////////////
jaList = new List <int>();
arList = new List <Double>();
lbMatrixList.Add(0.0);
ubMatrixList.Add(1.0);
jaList.Add(colInd2);
arList.Add(1);
jaList.Add(nbNode1 * nbNode2 + ij * nbEdge2 + kl);
arList.Add(-1);
indiceH[rownum] = jaList.ToArray();
valeurH[rownum] = arList.ToArray();
rownum++;
////////////////////////////////////////
/* jaList = new List<int>();
* arList = new List<Double>();
* lbMatrixList.Add(-1.0);
* ubMatrixList.Add(1.0);
*
* jaList.Add(colInd);
* arList.Add(1);
* jaList.Add(colInd2);
* arList.Add(1);
* jaList.Add(nbNode1 * nbNode2 + ij * nbEdge2 + kl);
* arList.Add(-1);
*
* indiceH[rownum] = jaList.ToArray();
* valeurH[rownum] = arList.ToArray();
* rownum++;*/
}
}
#endregion
double[] lb = lbMatrixList.ToArray();
double[] ub = ubMatrixList.ToArray();
Int32 res = ilpMatrix.AddRows(lb, ub, indiceH, valeurH);
// add the objective function
objCoef = objList.ToArray();
cplex.AddMinimize(cplex.ScalProd(x, objCoef));
}
catch (ILOG.Concert.Exception e)
{
System.Console.WriteLine("Concert exception '" + e + "' caught");
}
}
public static void Main(string[] args)
{
if (args.Length != 2)
{
Usage();
return;
}
bool ismip = false;
try {
Cplex cplex = new Cplex();
// Evaluate command line option and set optimization method accordingly.
switch (args[1].ToCharArray()[0])
{
case 'c': cplex.SetParam(Cplex.Param.OptimalityTarget,
Cplex.OptimalityTarget.OptimalConvex);
break;
case 'f': cplex.SetParam(Cplex.Param.OptimalityTarget,
Cplex.OptimalityTarget.FirstOrder);
break;
case 'g': cplex.SetParam(Cplex.Param.OptimalityTarget,
Cplex.OptimalityTarget.OptimalGlobal);
break;
default: Usage();
return;
}
cplex.ImportModel(args[0]);
ismip = cplex.IsMIP();
if (cplex.Solve())
{
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine("Solution value = " + cplex.ObjValue);
IEnumerator matrixEnum = cplex.GetLPMatrixEnumerator();
matrixEnum.MoveNext();
ILPMatrix lp = (ILPMatrix)matrixEnum.Current;
double[] x = cplex.GetValues(lp);
for (int j = 0; j < x.Length; ++j)
{
System.Console.WriteLine("Variable " + j + ": Value = " + x[j]);
}
}
cplex.End();
}
catch (ILOG.CPLEX.CplexModeler.Exception e) {
if (args[1].ToCharArray()[0] == 'c' &&
e.GetStatus() == 5002)
{
/* Status 5002 is CPXERR_Q_NOT_POS_DEF */
if (ismip)
{
System.Console.WriteLine("Problem is not convex. Use argument g to get global optimum.");
}
else
{
System.Console.Write("Problem is not convex. Use argument f to get local optimum ");
System.Console.WriteLine("or g to get global optimum.");
}
}
else if (args[1].ToCharArray()[0] == 'f' &&
e.GetStatus() == 1017 &&
ismip)
{
/* Status 1017 is CPXERR_NOT_FOR_MIP */
System.Console.Write("Problem is a MIP, cannot compute local optima satifying ");
System.Console.WriteLine("the first order KKT.");
System.Console.WriteLine("Use argument g to get the global optimum.");
}
else
{
System.Console.WriteLine("Cplex exception '" + e + "' caught");
}
}
catch (ILOG.Concert.Exception e) {
System.Console.WriteLine("Concert exception caught: " + e);
}
}
// GED formulation from the paper
// https://ieeexplore.ieee.org/document/1642656
public override void BLPjusticehero()
{
int nbNode1 = graph1.ListNodes.Count;
int nbNode2 = graph2.ListNodes.Count;
int N = nbNode1 + nbNode2; // nombre de noeuds du graphe d'édition
// #region
//création matrices de placement standard A0 et A1
Graph gridg1 = new Graph();
Graph gridg2 = new Graph();
Type typeNodeLabel = graph1.ListNodes[0].Label.GetType();
object objNode = Activator.CreateInstance(typeNodeLabel);
Graphs.Label nodeepslabel = (Graphs.Label)objNode;
nodeepslabel.Id = ConstantsAC.EPS_ID;
Type typeEdgeLabel = null;
object objEdge = null;
Graphs.Label edgeepslabel = null;
if (graph1.ListEdges.Count > 0)
{
typeEdgeLabel = graph1.ListEdges[0].Label.GetType();
objEdge = Activator.CreateInstance(typeEdgeLabel);
edgeepslabel = (Graphs.Label)objEdge;
edgeepslabel.Id = ConstantsAC.EPS_ID;
}
if (graph2.ListEdges.Count > 0)
{
typeEdgeLabel = graph2.ListEdges[0].Label.GetType();
objEdge = Activator.CreateInstance(typeEdgeLabel);
edgeepslabel = (Graphs.Label)objEdge;
edgeepslabel.Id = ConstantsAC.EPS_ID;
}
if (graph1.ListEdges.Count == 0 && graph2.ListEdges.Count == 0)
{
Console.Out.WriteLine("error no edges random edge label alkane");
edgeepslabel = (Graphs.Label) new LabelEdgeAlkane();
edgeepslabel.Id = ConstantsAC.EPS_ID;
}
//else
//{
//edgeepslabel = (Graphs.Label)new LabelEdgeAlkane();
//edgeepslabel.Id = ConstantsAC.EPS_ID;
//}
for (int i = 0; i < nbNode1; i++)
{
gridg1.addNode(graph1.ListNodes[i]);
}
for (int i = 0; i < graph1.ListEdges.Count; i++)
{
gridg1.addEdge(graph1.ListEdges[i]);
}
// ajout des noeuds "virtuels" au graphe g1, pour que g1 corresponde au placement standard dans le graphe d'édition (A0)
for (int i = nbNode1; i < N; i++)
{
Node n = new Node((i + 2).ToString());
gridg1.addNode(n);
n.Label = nodeepslabel;
n.Label.Id = ConstantsAC.EPS_ID;
// LabelEdgeLetter
//n.Label = new Graphs.GenericLabel();
//n.Label.Id = n.Id;
}
MatrixLibrary.Matrix A0 = gridg1.calculateAdjacencyMatrix(); // création matrice d'adajcence de g1
// idem pour g2 (A1)
for (int i = 0; i < nbNode2; i++)
{
gridg2.addNode(graph2.ListNodes[i]);
}
for (int i = 0; i < graph2.ListEdges.Count; i++)
{
gridg2.addEdge(graph2.ListEdges[i]);
}
for (int i = nbNode2; i < N; i++)
{
Node n = new Node((i + 2).ToString());
gridg2.addNode(n);
n.Label = nodeepslabel;//new LabelNodeMutagen();
n.Label.Id = ConstantsAC.EPS_ID;
//n.Label = new Graphs.GenericLabel();
//n.Label.Id = n.Id;
}
MatrixLibrary.Matrix A1 = gridg2.calculateAdjacencyMatrix(); // création matrice d'adajcence de g2
// les graphes vont être étiquetés avec un label LabelNodeMolecule (pour les noeuds) et LabelEdgeMolecule (pour les arrêtes)
// cela va nous permettre d'utiliser notre propre méthode "dissimilarity" pour les noeuds et arrêtes
// gridg1.DynamicCastLabel(graph1.ListNodes[0].Label, graph1.ListEdges[0].Label);
// gridg2.DynamicCastLabel(graph2.ListNodes[0].Label, graph2.ListEdges[0].Label);
// nb variables du pb : matrices P(N*N), S(N*N) et T(N*N)
int nbCols = 3 * (N * N);
// nb contraintes du pb
int nbRows = N * N + N + N;
List <double> objList = new List <double>();
List <string> colNameList = new List <string>();
// coût des opérations d'édition des sommets (coeff de P dans la formule de la distance d'édition)
for (int i = 0; i < N; i++)
{
for (int j = 0; j < N; j++)
{
double costNode = gridg1.ListNodes[i].Label.dissimilarity(gridg2.ListNodes[j].Label);
objList.Add(costNode);
//colNameList.Add("P[" + gridg1.ListNodes[i].Id + "][" + gridg2.ListNodes[j].Id + "]");
colNameList.Add("x_" + gridg1.ListNodes[i].Id + "," + gridg2.ListNodes[j].Id + "");
}
}
// coût des opérations d'édition des arrêtes (coeffs de S et T)
//Edge ee = new Edge((0).ToString());
//ee.Label = new LabelEdgeMutagen();
//ee.Label.Id = ConstantsAC.EPS_ID;
// coeff de S
for (int i = 0; i < N; i++)
{
for (int j = 0; j < N; j++)
{
// dans notre cas, l'opération est soit 0->1 ou 1->0 (insertion ou suppression d'une arrête)
// double costNode = ee.Label.dissimilarity(ee.Label) / 2.0;
double costNode = edgeepslabel.dissimilarity(edgeepslabel) / 2.0;
//double costNode = 0.5 / 2.0;
objList.Add(costNode);
colNameList.Add("S[" + gridg1.ListNodes[i].Id + "][" + gridg2.ListNodes[j].Id + "]");
}
}
// coeff de T
for (int i = 0; i < N; i++)
{
for (int j = 0; j < N; j++)
{
// dans notre cas, l'opération est soit 0->1 ou 1->0 (insertion ou suppression d'une arrête)
//double costNode = ee.Label.dissimilarity(ee.Label) / 2.0;
double costNode = edgeepslabel.dissimilarity(edgeepslabel) / 2.0;
// double costNode = 0.5 / 2.0;
objList.Add(costNode);
colNameList.Add("T[" + gridg1.ListNodes[i].Id + "][" + gridg2.ListNodes[j].Id + "]");
}
}
try
{
// Cplex cplex = new Cplex(); // creation du modèle CPLEX
//ILPMatrix lp_matrix = cplex.AddLPMatrix(); // matrice du pb (initialisée à 0 colonnes et 0 lignes)
cplex = new Cplex();
ilpMatrix = cplex.AddLPMatrix();
ColumnArray colonnes = cplex.ColumnArray(ilpMatrix, nbCols); // définition des variables-colonnes du pb
// ajout des variables-colonnes dans la matrice du pb (avec définition des bornes: P[i][j] = 0 ou 1, idem avec S et T)
INumVar[] x = cplex.NumVarArray(colonnes, 0, 1, NumVarType.Bool, colNameList.ToArray());
INumVar[,] P = new INumVar[N, N];
INumVar[,] S = new INumVar[N, N];
INumVar[,] T = new INumVar[N, N];
for (int i = 0; i < N; i++)
{
for (int j = 0; j < N; j++)
{
P[i, j] = x[(N * i) + j];
}
}
// indice de S et T dans x (utilisés lors de la définition des contraintes)
int indicedebutS = N * N; // indice du 1er élément de S dans x
int indicedebutT = 2 * (N * N); // indice du 1er élément de T dans x
for (int i = 0; i < N; i++)
{
for (int j = 0; j < N; j++)
{
S[i, j] = x[indicedebutS + (N * i) + j];
}
}
for (int i = 0; i < N; i++)
{
for (int j = 0; j < N; j++)
{
T[i, j] = x[indicedebutT + (N * i) + j];
}
}
objCoef = objList.ToArray();
// ajout de la fonction objectif du pb
cplex.AddMinimize(cplex.ScalProd(x, objCoef));
// contrainte n°1
for (int i = 0; i < N; i++)
{
int[] coeffsA0 = new int[N]; // vecteur des coeffs ligne i de A0
INumVar[] coeffsP_A1 = new INumVar[N]; // vecteur des coeffs ligne i de P
for (int c = 0; c < N; c++)
{
coeffsA0[c] = (int)A0[i, c];
coeffsP_A1[c] = P[i, c];
}
for (int j = 0; j < N; j++)
{
INumVar[] coeffsP = new INumVar[N]; // vecteur des coeffs colonne j de P
int[] coeffsA1 = new int[N]; // vecteur des coeffs colonne j de A1
for (int c = 0; c < N; c++)
{
coeffsP[c] = P[c, j];
coeffsA1[c] = (int)A1[c, j];
}
cplex.AddEq(cplex.Sum(
cplex.Diff(
cplex.ScalProd(coeffsP, coeffsA0), cplex.ScalProd(coeffsP_A1, coeffsA1)),
cplex.Diff(
S[i, j], T[i, j]))
, 0);
/* (ANCIEN PRODUIT TERME A TERME)
* cplex.AddEq(cplex.Sum(
* cplex.Diff(
* cplex.Prod(A0[i,j],P[i,j]),cplex.Prod(P[i,j],A1[i,j])),
* cplex.Diff(
* S[i, j], T[i, j]))
* , 0); */
}
}
// contrainte n°2 (somme des lignes dans P = 1 et somme des colonnes dans P = 1)
for (int i = 0; i < N; i++)
{
INumVar[] sommeLignes = new INumVar[N];
INumVar[] sommeColonnes = new INumVar[N];
for (int j = 0; j < N; j++)
{
sommeLignes[j] = x[N * i + j];
sommeColonnes[j] = x[N * j + i];
}
cplex.AddEq(cplex.Sum(sommeLignes), 1);
cplex.AddEq(cplex.Sum(sommeColonnes), 1);
}
}
catch (ILOG.Concert.Exception e)
{
System.Console.WriteLine("Concert exception `" + e + "` caught");
}
}
