internal static void BuildModelByColumn(IMPModeler model,
Data data,
INumVar[] Buy,
NumVarType type)
{
int nFoods = data.nFoods;
int nNutrs = data.nNutrs;
IObjective cost = model.AddMinimize();
IRange[] constraint = new IRange[nNutrs];
for (int i = 0; i < nNutrs; i++)
{
constraint[i] = model.AddRange(data.nutrMin[i], data.nutrMax[i]);
}
for (int j = 0; j < nFoods; j++)
{
Column col = model.Column(cost, data.foodCost[j]);
for (int i = 0; i < nNutrs; i++)
{
col = col.And(model.Column(constraint[i], data.nutrPerFood[i][j]));
}
Buy[j] = model.NumVar(col, data.foodMin[j], data.foodMax[j], type);
}
}
internal static void BuildModelByRow(IModeler model,
Data data,
INumVar[] Buy,
NumVarType type) {
int nFoods = data.nFoods;
int nNutrs = data.nNutrs;
for (int j = 0; j < nFoods; j++) {
Buy[j] = model.NumVar(data.foodMin[j], data.foodMax[j], type);
}
model.AddMinimize(model.ScalProd(data.foodCost, Buy));
for (int i = 0; i < nNutrs; i++) {
model.AddRange(data.nutrMin[i],
model.ScalProd(data.nutrPerFood[i], Buy),
data.nutrMax[i]);
}
}
internal static void BuildModelByRow(IModeler model,
Data data,
INumVar[] Buy,
NumVarType type)
{
int nFoods = data.nFoods;
int nNutrs = data.nNutrs;
for (int j = 0; j < nFoods; j++)
{
Buy[j] = model.NumVar(data.foodMin[j], data.foodMax[j], type);
}
model.AddMinimize(model.ScalProd(data.foodCost, Buy));
for (int i = 0; i < nNutrs; i++)
{
model.AddRange(data.nutrMin[i],
model.ScalProd(data.nutrPerFood[i], Buy),
data.nutrMax[i]);
}
}
internal static void BuildModelByColumn(IMPModeler model,
Data data,
INumVar[] Buy,
NumVarType type)
{
int nFoods = data.nFoods;
int nNutrs = data.nNutrs;
IObjective cost = model.AddMinimize();
IRange[] constraint = new IRange[nNutrs];
for (int i = 0; i < nNutrs; i++) {
constraint[i] = model.AddRange(data.nutrMin[i], data.nutrMax[i]);
}
for (int j = 0; j < nFoods; j++) {
Column col = model.Column(cost, data.foodCost[j]);
for (int i = 0; i < nNutrs; i++) {
col = col.And(model.Column(constraint[i], data.nutrPerFood[i][j]));
}
Buy[j] = model.NumVar(col, data.foodMin[j], data.foodMax[j], type);
}
}
public static void Main(string[] args)
{
try {
string filename = "../../../../examples/data/diet.dat";
bool byColumn = false;
NumVarType varType = NumVarType.Float;
for (int i = 0; i < args.Length; i++)
{
if (args[i].ToCharArray()[0] == '-')
{
switch (args[i].ToCharArray()[1])
{
case 'c':
byColumn = true;
break;
case 'i':
varType = NumVarType.Int;
break;
default:
Usage();
return;
}
}
else
{
filename = args[i];
break;
}
}
Data data = new Data(filename);
int nFoods = data.nFoods;
int nNutrs = data.nNutrs;
// Build model
Cplex cplex = new Cplex();
INumVar[] Buy = new INumVar[nFoods];
if (byColumn)
{
BuildModelByColumn(cplex, data, Buy, varType);
}
else
{
BuildModelByRow(cplex, data, Buy, varType);
}
// Solve model
if (cplex.Solve())
{
System.Console.WriteLine();
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine();
System.Console.WriteLine(" cost = " + cplex.ObjValue);
for (int i = 0; i < nFoods; i++)
{
System.Console.WriteLine(" Buy" + i + " = " + cplex.GetValue(Buy[i]));
}
System.Console.WriteLine();
}
cplex.End();
}
catch (ILOG.Concert.Exception ex) {
System.Console.WriteLine("Concert Error: " + ex);
}
catch (InputDataReader.InputDataReaderException ex) {
System.Console.WriteLine("Data Error: " + ex);
}
catch (System.IO.IOException ex) {
System.Console.WriteLine("IO Error: " + ex);
}
}
public INumVar[] NumVarArray(int num, double lb, double ub, NumVarType type)
{
double[] ubs = new double[num];
double[] lbs = new double[num];
NumVarType[] types = new NumVarType[num];
for (int i = 0; i < num; i++)
{
lbs[i] = lb;
ubs[i] = ub;
types[i] = type;
}
return NumVarArray(num, lbs, ubs, types, null);
}
public VoidClass Conversion(INumVar var, NumVarType type)
{
var.var.Set(GRB.CharAttr.VType, type.type);
return new VoidClass();
}
public INumVar NumVar(Column col, double lb, double ub, NumVarType type)
{
INumVar result = new INumVar();
result.var = _model.AddVar(lb, ub, col.objCoef, type.type, col.column, null);
return result;
}
public INumVar NumVar(double lb, double ub, NumVarType type, string name)
{
INumVar result = new INumVar();
result.name = name;
result.var = _model.AddVar(lb, ub, 0, type.type, name);
return result;
}
public INumVar NumVar(double lb, double ub, NumVarType type)
{
INumVar result = new INumVar();
result.var = _model.AddVar(lb, ub, 0, type.type, null);
return result;
}
public INumVar[] NumVarArray(int num, double[] lbs, double[] ubs, NumVarType[] types, string[] names)
{
INumVar[] result = new INumVar[num];
char[] gurobi_types = null;
if (types != null)
{
gurobi_types = new char[num];
for (int i = 0; i < num; i++)
{
gurobi_types[i] = types[i].type;
}
}
GRBVar[] vars = _model.AddVars(lbs, ubs, null, gurobi_types, names);
for (int i = 0; i < num; i++)
{
result[i] = new INumVar();
result[i].var = vars[i];
}
return result;
}
public INumVar[] NumVarArray(int num, double[] lbs, double[] ubs, NumVarType[] types)
{
return NumVarArray(num, lbs, ubs, types, null);
}
static void Main(string[] args)
{
int nSamples = 0; // Number of samples
int nMutGenes = 0; // Number of mutation genes
int nExpGenes = 0; // Number of expression genes
int nVar = 0; // Number of variables in MILP
int nPathways = 5; // Number of pathways
int nConstraints = 0; // Number of constraints in MILP
Data data = new Data();
// Loads input data.
data.ReadData("../../inputFile.txt");
nSamples = data.mutMatrix.Length;
nMutGenes = data.mutMatrix[0].Length;
nExpGenes = data.connectMat.Length;
// Total number of decision variables:
// pM --> nMutGenes * nPathways
// pE --> nExpGenes * nPathways
// aM --> nSamples * nPathways
// fM --> nSamples * nPathways
nVar = (nMutGenes * nPathways) + (nExpGenes * nPathways) + 2 * (nSamples * nPathways);
// Instance of cplex model.
Cplex cplex = new Cplex();
/* We were having issues with "Out of Memory" errors as we increased the number of samples and number of genes
* To address this, we set parameter NodeFileInd = 3 --> this indicates that node info from MIP optimizer will be compressed
* and written to files instead of accessing the computer memory during the simulation run
*
* */
cplex.SetParam(Cplex.IntParam.NodeFileInd, 3);
// Sets names of decision variables.
string[] name = new string[nVar];
for (int i = 1; i <= nVar; i++)
{
name[i - 1] = "x" + i.ToString();
}
// Sets type, lower and upper bound of decision variables.
NumVarType[] varType = new NumVarType[nVar];
double[] lb = new double[nVar];
double[] ub = new double[nVar];
for (int i = 0; i < nMutGenes * nPathways; i++)
{
// Variable pM is binary.
varType[i] = NumVarType.Bool;
lb[i] = 0;
ub[i] = 1;
}
for (int i = nMutGenes * nPathways; i < (nMutGenes * nPathways) + (nExpGenes * nPathways); i++)
{
// Variable pE is real number.
varType[i] = NumVarType.Float;
lb[i] = 0;
ub[i] = System.Double.MaxValue;
}
for (int i = (nMutGenes * nPathways) + (nExpGenes * nPathways); i < nVar; i++)
{
// Variables aM and fM are binary.
varType[i] = NumVarType.Bool;
lb[i] = 0;
ub[i] = 1;
}
// Decision Variables.
INumVar[] x = cplex.NumVarArray(nVar, lb, ub, varType, name);
// Coeficients of objective function.
double[] objvals = new double[nVar];
int contobjvals = 0;
int idMap = 0; // Mapping index.
// Variable pM.
int[][] pM = new int[nMutGenes][]; // Mapping matrix pM.
for (int i = 0; i < nMutGenes; i++)
{
pM[i] = new int[nPathways];
for (int j = 0; j < nPathways; j++)
{
// Mapping....
pM[i][j] = idMap;
idMap++;
objvals[contobjvals] = 0;
for (int k = 0; k < nSamples; k++)
{
// Weight associated with first component of objective function = 0.1.
objvals[contobjvals] += 0.1 * data.mutMatrix[k][i];
}
contobjvals++;
}
}
// Variable pE.
int[][] pE = new int[nExpGenes][];
for (int i = 0; i < nExpGenes; i++)
{
pE[i] = new int[nPathways];
for (int j = 0; j < nPathways; j++)
{
// Mapping....
pE[i][j] = idMap;
idMap++;
// Weight associated with second component of objective function = 0.9.
objvals[contobjvals] = -0.9;
contobjvals++;
}
}
// Variable aM.
int[][] aM = new int[nSamples][];
for (int i = 0; i < nSamples; i++)
{
aM[i] = new int[nPathways];
for (int j = 0; j < nPathways; j++)
{
// Mapping....
aM[i][j] = idMap;
idMap++;
// Weight associated with first component of objective function = 0.1.
objvals[contobjvals] = -0.1;
contobjvals++;
}
}
// Variable fM.
int[][] fM = new int[nSamples][];
for (int i = 0; i < nSamples; i++)
{
fM[i] = new int[nPathways];
for (int j = 0; j < nPathways; j++)
{
// Mapping....
fM[i][j] = idMap;
idMap++;
// Weight associated with first component of objective function = 0.1.
objvals[contobjvals] = 0.1;
contobjvals++;
}
}
// Defines the cost function as a minimization of decision variables with corresponding cost coefficients.
cplex.Add(cplex.Minimize(cplex.ScalProd(x, objvals)));
nConstraints = nMutGenes + nExpGenes + 2 * nPathways + nSamples * (nPathways - 1) + (nSamples * nPathways) + (nPathways * nExpGenes); // Total number of constraints.
IRange[] constraint = new IRange[nConstraints];
int contconstraints = 0;
INumExpr[] Expr = null;
// Constraints C1.
Expr = new INumExpr[nPathways];
for (int i = 0; i < nMutGenes; i++)
{
for (int j = 0; j < nPathways; j++)
{
Expr[j] = x[pM[i][j]];
}
// Constraints of the form sum(pM) = 1.
constraint[contconstraints] = cplex.AddRange(1, 1); // Defines right hand side (= 1).
constraint[contconstraints].Expr = cplex.Sum(Expr); // Defines left hand side (sum(pM)).
contconstraints++;
}
// Constraints C2.
Expr = new INumExpr[nPathways];
for (int i = 0; i < nExpGenes; i++)
{
for (int j = 0; j < nPathways; j++)
{
Expr[j] = x[pE[i][j]];
}
// Constraints of the form sum(pE) > 0.
constraint[contconstraints] = cplex.AddRange(0.000001, System.Double.MaxValue); // Defines right hand side (> 0).
constraint[contconstraints].Expr = cplex.Sum(Expr); // Defines left hand side (sum(pE)).
contconstraints++;
}
// Constraints C3.
Expr = new INumExpr[nMutGenes];
for (int i = 0; i < nPathways; i++)
{
for (int j = 0; j < nMutGenes; j++)
{
Expr[j] = x[pM[j][i]];
}
// Constraints of the form sum(pM) >= 1.
constraint[contconstraints] = cplex.AddRange(1, System.Double.MaxValue); // Defines right hand side (>= 1).
constraint[contconstraints].Expr = cplex.Sum(Expr); // Defines left hand side (sum(pM)).
contconstraints++;
}
// Constraints C4.
int id = nMutGenes * nPathways;
Expr = new INumExpr[nExpGenes];
for (int i = 0; i < nPathways; i++)
{
for (int j = 0; j < nExpGenes; j++)
{
Expr[j] = x[pE[j][i]];
}
// Constraints of the form sum(pE) > 0.
constraint[contconstraints] = cplex.AddRange(0.000001, System.Double.MaxValue); // Defines right hand side (> 0).
constraint[contconstraints].Expr = cplex.Sum(Expr); // Defines left hand side (sum(pE)).
contconstraints++;
}
// Constraints C5.
id = nMutGenes * nPathways + nExpGenes * nPathways;
for (int i = 0; i < nSamples; i++)
{
// Constraints of the form aM - aM >= 0.
for (int j = 0; j < (nPathways - 1); j++)
{
constraint[contconstraints] = cplex.AddRange(0, System.Double.MaxValue); // Defines right hand side (>= 0).
constraint[contconstraints].Expr = cplex.Sum(cplex.Prod(1.0, x[aM[i][j]]), cplex.Prod(-1.0, x[aM[i][j + 1]])); // Defines left hand side (aM - aM).
contconstraints++;
}
}
// Constraints C6.
Expr = new INumExpr[nMutGenes + 2];
for (int i = 0; i < nSamples; i++) // Goes along lines of mutation matrix.
{
for (int k = 0; k < nPathways; k++)
{
for (int j = 0; j < nMutGenes; j++) // Goes along columns of mutation matrix.
{
Expr[j] = cplex.Prod(data.mutMatrix[i][j], x[pM[j][k]]);
}
Expr[nMutGenes] = cplex.Prod(1.0, x[fM[i][k]]);
Expr[nMutGenes + 1] = cplex.Prod(-1.0, x[aM[i][k]]);
// Constraints of the form sum(mutMat*pM) + fM - aM >= 0.
constraint[contconstraints] = cplex.AddRange(0, System.Double.MaxValue); // Defines right hand side (>= 0).
constraint[contconstraints].Expr = cplex.Sum(Expr); // Defines left hand side (sum(mutMat*pM) + fM - aM).
contconstraints++;
}
}
// Constraints C7.
Expr = new INumExpr[nMutGenes + 1];
for (int i = 0; i < nPathways; i++)
{
for (int j = 0; j < nExpGenes; j++)
{
for (int k = 0; k < nMutGenes; k++)
{
Expr[k] = cplex.Prod(-data.connectMat[j][k], x[pM[k][i]]);
}
Expr[nMutGenes] = cplex.Prod(1.0, x[pE[j][i]]);
// Constraints of the form pE - sum(connectMat*pM) = 0.
constraint[contconstraints] = cplex.AddRange(0, 0); // Defines right hand side (= 0).
constraint[contconstraints].Expr = cplex.Sum(Expr); // Defines left hand side (pE - sum(connectMat*pM)).
contconstraints++;
}
}
// Writes file with MILP model formulation.
cplex.ExportModel("MILP.lp");
try
{
if (cplex.Solve())
{
// Retrieves optimal values of decision variables.
double[] xx = cplex.GetValues(x);
// Displays solution info on command window.
cplex.Output().WriteLine("Solution status=" + cplex.GetStatus());
cplex.Output().WriteLine("Solution value = " + cplex.ObjValue);
// Writes output to txt file.
StreamWriter objWriter = new StreamWriter("Result.txt");
int cont = 0;
string sLine = "";
int nvars = xx.Length;
objWriter.WriteLine("Total cost");
objWriter.WriteLine(cplex.ObjValue.ToString());
objWriter.WriteLine("");
objWriter.WriteLine("Matrix pM");
objWriter.WriteLine("");
for (int i = 0; i < nMutGenes; i++)
{
sLine = "";
for (int j = 0; j < nPathways; j++)
{
sLine += xx[cont].ToString() + "\t";
cont++;
}
objWriter.WriteLine(sLine);
}
// Value of second term of objective function (sum of pE's).
double sumPE = 0.0;
objWriter.WriteLine("");
objWriter.WriteLine("Matrix pE");
objWriter.WriteLine("");
for (int i = 0; i < nExpGenes; i++)
{
sLine = "";
for (int j = 0; j < nPathways; j++)
{
sLine += xx[cont].ToString() + "\t";
cont++;
// Computes running sum of pE's.
sumPE = sumPE + xx[cont];
}
objWriter.WriteLine(sLine);
}
objWriter.WriteLine("");
objWriter.WriteLine("Sum pE");
objWriter.WriteLine(sumPE.ToString());
objWriter.WriteLine("");
objWriter.WriteLine("");
objWriter.WriteLine("Matrix aM");
objWriter.WriteLine("");
for (int i = 0; i < nSamples; i++)
{
sLine = "";
for (int j = 0; j < nPathways; j++)
{
sLine += xx[cont].ToString() + "\t";
cont++;
}
objWriter.WriteLine(sLine);
}
objWriter.WriteLine("");
objWriter.WriteLine("Matrix fM");
objWriter.WriteLine("");
for (int i = 0; i < nSamples; i++)
{
sLine = "";
for (int j = 0; j < nPathways; j++)
{
sLine += xx[cont].ToString() + "\t";
cont++;
}
objWriter.WriteLine(sLine);
}
objWriter.Close();
// Writes optimal solution info to file.
cplex.WriteSolution("solution");
}
else
{
cplex.GetCplexStatus();
}
cplex.End();
}
catch (ILOG.Concert.Exception e)
{
System.Console.WriteLine("Concert exception '" + e + "' caught");
}
}
private double one_tsp(int dim, int [][] matrix, int [] path)
{
int[] lo = new int[dim];
for (int i = 0; i < dim; i++)
{
lo[i] = 1;
}
Cplex cplex = new Cplex();
NumVarType varType = NumVarType.Bool;
INumVar[][] x = new INumVar[dim][];
for (int i = 0; i < dim; i++)
{
x[i] = cplex.NumVarArray(dim, 0, 1);
}
for (int i = 0; i < dim; i++)
{
for (int j = 0; j < dim; j++)
{
x[i][j] = cplex.BoolVar();
}
}
for (int j = 0; j < dim; j++)
{
INumExpr xcolSum = cplex.NumExpr();
for (int i = 0; i < dim; i++)
{
xcolSum = cplex.Sum(xcolSum, x[i][j]);
}
cplex.AddEq(lo[j], xcolSum);
}
varType = NumVarType.Float;
INumVar[] u = new INumVar[dim];
for (int j = 0; j < dim; j++)
{
u[j] = cplex.NumVar(0, 100000);
}
for (int j = 1; j < dim; j++)
{
cplex.AddGe(u[j], 0);
}
for (int i = 1; i < dim; i++)
{
for (int j = 1; j < dim; j++)
{
if (i != j)
{
cplex.AddLe(cplex.Sum(cplex.Diff(u[i], u[j]), cplex.Prod(dim, x[i][j])), dim - 1);
}
}
}
for (int i = 0; i < dim; i++)
{
INumExpr xrowSum = cplex.NumExpr();
for (int j = 0; j < dim; j++)
{
xrowSum = cplex.Sum(xrowSum, x[i][j]);
}
cplex.AddEq(lo[i], xrowSum);
}
INumExpr costSum = cplex.NumExpr();
for (int i = 0; i < dim; i++)
{
for (int j = 0; j < dim; j++)
{
costSum = cplex.Sum(costSum, cplex.Prod(x[i][j], matrix[i][j]));
}
}
cplex.AddMinimize(costSum);
try
{
if (cplex.Solve())
{
//MessageBox.Show("Solution status = " + cplex.GetStatus());
//MessageBox.Show("cost = " + cplex.ObjValue);
int ipath = 0;
int depo = -1;
for (int i = dim - 1; i >= 0; i--)
{
for (int j = 0; j < dim; j++)
{
if (Convert.ToInt16(cplex.GetValue(x[i][j])) == 1)
{
depo = i;
}
}
}
path[ipath] = depo;
ipath++;
while (depo > -1)
{
for (int j = 0; j < dim; j++)
{
if (Convert.ToInt16(cplex.GetValue(x[path[ipath - 1]][j])) == 1)
{
path[ipath] = j;
ipath++;
if (j == depo)
{
depo = -1;
}
break;
}
}
}
return(cplex.ObjValue);
}
cplex.End();
}
catch (ILOG.Concert.Exception ex)
{
System.Console.WriteLine("Concert Error: " + ex);
}
return(-1);
}
private void decomp(int dim, int kts, int[][] dist, List <int> WorkList)
{
int[] lo = new int[dim];
int dk = dim * kts;
for (int i = 0; i < dim; i++)
{
lo[i] = 1;
}
Cplex cplex = new Cplex();
NumVarType varType = NumVarType.Bool;
INumVar[][] x = new INumVar[dim][];
for (int i = 0; i < dim; i++)
{
x[i] = cplex.NumVarArray(dk, 0, 1);
}
for (int i = 0; i < dim; i++)
{
for (int j = 0; j < dk; j++)
{
x[i][j] = cplex.BoolVar();
}
}
//****************************************
//Что тут происходит?
for (int j = 0; j < dim; j++)
{
INumExpr xcolSum = cplex.NumExpr();
for (int k = 0; k < kts; k++)
{
for (int i = 0; i < dim; i++)
{
xcolSum = cplex.Sum(xcolSum, x[i][k * dim + j]);
}
}
cplex.AddEq(lo[j], xcolSum);
}
varType = NumVarType.Float;
INumVar[] u = new INumVar[dk];
for (int j = 0; j < dk; j++)
{
u[j] = cplex.NumVar(0, 100000);
}
for (int j = 1; j < dk; j++)
{
cplex.AddGe(u[j], 0);
}
for (int k = 0; k < kts; k++)
{
for (int i = 1; i < dim; i++)
{
for (int j = 1; j < dim; j++)
{
if (i != j)
{
if (kts == 1)
{
cplex.AddLe(cplex.Sum(cplex.Diff(u[k * dim + i], u[k * dim + j]), cplex.Prod(dim, x[i][k * dim + j])), dim - 1);
}
else
{
cplex.AddLe(cplex.Sum(cplex.Diff(u[k * dim + i], u[k * dim + j]), cplex.Prod(dim, x[i][k * dim + j])), dim);
}
}
}
}
}
for (int i = 0; i < dim; i++)
{
INumExpr xrowSum = cplex.NumExpr();
for (int j = 0; j < dk; j++)
{
xrowSum = cplex.Sum(xrowSum, x[i][j]);
}
cplex.AddEq(lo[i], xrowSum);
}
//Условия независимости кластеров
if (kts > 1)
{
int[] a = new int[kts + 1];
for (int k = 1; k < kts; k++)
{
if (k > 1 && k < kts - 1)
{
continue;
}
int p;
for (int i = 1; i <= k; i++)
{
a[i] = i;
}
p = k;
while (p >= 1)
{
for (int m = 0; m < dim; m++)
{
INumExpr xcolrowSum = cplex.NumExpr();
for (int j = 1; j <= kts; j++)
{
bool row = false;
for (int i = 1; i <= k; i++)
{
if (a[i] == j)
{
row = true;
}
}
if (row)
{
for (int t = 0; t < dim; t++)
{
xcolrowSum = cplex.Sum(xcolrowSum, x[m][(j - 1) * dim + t]);
}
}
else
{
for (int t = 0; t < dim; t++)
{
xcolrowSum = cplex.Sum(xcolrowSum, x[t][(j - 1) * dim + m]);
}
}
}
cplex.AddLe(xcolrowSum, lo[m]);
}
if (a[k] == kts)
{
p--;
}
else
{
p = k;
}
if (p >= 1)
{
for (int i = k; i >= p; i--)
{
a[i] = a[p] + i - p + 1;
}
}
}
}
}
INumExpr costSum = cplex.NumExpr();
INumExpr[] costSum1 = new INumExpr[kts];
if (kts == 1)
{
for (int i = 0; i < dim; i++)
{
for (int j = 0; j < dim; j++)
{
costSum = cplex.Sum(costSum, cplex.Prod(x[i][j], dist[i][j]));
}
}
cplex.AddMinimize(costSum);
}
else
{
for (int k = 0; k < kts; k++)
{
costSum1[k] = cplex.NumExpr();
for (int i = 0; i < dim; i++)
{
for (int j = 0; j < dim; j++)
{
costSum1[k] = cplex.Sum(costSum1[k], cplex.Prod(x[i][k * dim + j], dist[i][j]));
}
}
//cplex.AddLe(costSum1[k], costSum);
}
costSum = cplex.Max(costSum1);
cplex.AddMinimize(costSum);
}
try
{
if (cplex.Solve())
{
textBox1.Text += "lambda = " + cplex.ObjValue + Environment.NewLine;
textBox1.Text += DateTime.Now.ToString() + Environment.NewLine;
WorkList.Clear();
int num_clust = 0;
for (int k = 0; k < kts; k++)
{
int dim1 = 0;
for (int i = 0; i < dim; i++)
{
for (int j = 0; j < dim; j++)
{
if (Convert.ToInt16(cplex.GetValue(x[i][k * dim + j])) == 1)
{
dim1++;
}
}
}
if (dim1 > 0)
{
num_clust++;
for (int i = 0; i < dim; i++)
{
for (int j = 0; j < dim; j++)
{
if (Convert.ToInt16(cplex.GetValue(x[i][k * dim + j])) == 1)
{
WorkList.Add(i);
break;
}
}
}
WorkList.Add(-1);
}
}
textBox1.Text += DateTime.Now.ToString() + Environment.NewLine;
}
else
{
textBox1.Text += "Нет решения" + Environment.NewLine;
textBox1.Text += DateTime.Now.ToString() + Environment.NewLine;
}
cplex.End();
}
catch (ILOG.Concert.Exception ex)
{
textBox1.Text += "Concert Error: " + ex + Environment.NewLine;
textBox1.Text += DateTime.Now.ToString() + Environment.NewLine;
}
}
