protected void InitRMPModel()
{
cost = RMPModel.AddMaximize();
var = new Dictionary <IALPDecision, INumVar> [Data.TimeHorizon];
DualValue1 = new double[Data.TimeHorizon][];
DualValue2 = new double[Data.TimeHorizon];
lowerbound = new double[Data.TimeHorizon][];
upperbound = new double[Data.TimeHorizon][];
#region //////////////生成约束//////////////
constraint1 = new IRange[Data.TimeHorizon][];
constraint2 = new IRange[Data.TimeHorizon];
for (int i = 0; i < Data.TimeHorizon; i++)
{
DualValue1[i] = new double[Data.RS.Count];
var[i] = new Dictionary <IALPDecision, INumVar>();
constraint1[i] = new IRange[Data.RS.Count];
lowerbound[i] = new double[Data.RS.Count];
upperbound[i] = new double[Data.RS.Count];
foreach (IALPResource re in Data.RS)
{
constraint1[i][Data.RS.IndexOf(re)] = RMPModel.AddRange(double.MinValue, (Data.InitialState as IALPState)[re]);
}
//constraint1[i][0].UB -= 0.3;
constraint2[i] = RMPModel.AddRange(1, 1);
}
#endregion
RMPModel.SetOut(this.SolverTextWriter);
}
//Affine Funciton Approximation
public static Cplex Build_CD1_Model(IALPFTMDP aff)
{
Cplex model = new Cplex();
IObjective cost = model.AddMaximize();
IRange[][] constraint1 = new IRange[aff.TimeHorizon][];
IRange[] constraint2 = new IRange[aff.TimeHorizon];
#region //////////////生成约束//////////////
for (int i = 0; i < aff.TimeHorizon; i++)
{
constraint1[i] = new IRange[aff.RS.Count];
foreach (IALPResource re in aff.RS)
{
if (i == 0)
{
constraint1[i][aff.RS.IndexOf(re)] = model.AddRange((aff.InitialState as IALPState)[re], (aff.InitialState as IALPState)[re]);
}
else
{
constraint1[i][aff.RS.IndexOf(re)] = model.AddRange(0, 0);
}
}
constraint2[i] = model.AddRange(1, 1);
}
#endregion
#region //////////////生成变量//////////////
for (int t = 0; t < aff.TimeHorizon; t++)
{
foreach (IALPState s in aff.SS)
{
foreach (IMDPDecision a in aff.GenDecisionSpace(s))
{
Column col = model.Column(cost, aff.Rt(t, a));
foreach (IALPResource re in aff.RS)
{
col = col.And(model.Column(constraint1[t][aff.RS.IndexOf(re)], (s as IALPState)[re]));
if (t < aff.TimeHorizon - 1)
{
col = col.And(model.Column(constraint1[t + 1][aff.RS.IndexOf(re)], (aff.Qti(t, re, a)) - (s as IALPState)[re]));
}
}
col = col.And(model.Column(constraint2[t], 1));
model.NumVar(col, 0, double.MaxValue, NumVarType.Float);
}
}
}
#endregion
return(model);
}
public static Cplex BuildDualModel(IFTMDP Ida)
{
Cplex model = new Cplex();
IObjective cost = model.AddMaximize();
IRange[][] constraint = new IRange[Ida.TimeHorizon][];
#region //////////////生成约束//////////////
for (int i = 0; i < Ida.TimeHorizon; i++)
{
constraint[i] = new IRange[Ida.SS.Count];
foreach (IMDPState s in Ida.SS)
{
if (i == 0 && s.Equals(Ida.InitialState))
{
constraint[i][Ida.SS.IndexOf(s)] = model.AddRange(1, 1);
}
else
{
constraint[i][Ida.SS.IndexOf(s)] = model.AddRange(0, 0);
}
}
}
#endregion
#region //////////////生成变量//////////////
for (int t = 0; t < Ida.TimeHorizon; t++)
{
foreach (IMDPState s in Ida.SS)
{
foreach (IMDPDecision a in Ida.GenDecisionSpace(s))
{
Column col = model.Column(cost, Ida.Reward(t, s, a));
col = col.And(model.Column(constraint[t][Ida.SS.IndexOf(s)], 1)); //插入Aj
if (t < Ida.TimeHorizon - 1)
{
foreach (IMDPState k in Ida.GenStateSpace(s, a))
{
col = col.And(model.Column(constraint[t + 1][Ida.SS.IndexOf(k)], -Ida.Prob(t, s, k, a))); //插入Aj
}
}
model.NumVar(col, 0, double.MaxValue, NumVarType.Float);
}
}
}
#endregion
model.SetOut(null);
return(model);
}
public static Cplex Build_CD3_Model(IALPFTMDP aff)
{
Cplex model = new Cplex();
IObjective cost = model.AddMaximize();
INumVar[][] var = new INumVar[aff.TimeHorizon][];
#region //////////////生成约束//////////////
IRange[][] constraint1 = new IRange[aff.TimeHorizon][];
IRange[] constraint2 = new IRange[aff.TimeHorizon];
for (int i = 0; i < aff.TimeHorizon; i++)
{
var[i] = new INumVar[aff.DS.Count];
constraint1[i] = new IRange[aff.RS.Count];
foreach (IALPResource re in aff.RS)
{
constraint1[i][aff.RS.IndexOf(re)] = model.AddRange(double.MinValue, (aff.InitialState as IALPState)[re]);
}
constraint2[i] = model.AddRange(1, 1);
}
#endregion
#region //////////////生成变量//////////////
for (int t = 0; t < aff.TimeHorizon; t++)
{
foreach (IALPDecision a in aff.DS)
{
//目标函数
Column col = model.Column(cost, aff.Rt(t, a));
//第一类约束
foreach (IALPResource re in aff.RS)
{
for (int k = t + 1; k < aff.TimeHorizon; k++)
{
col = col.And(model.Column(constraint1[k][aff.RS.IndexOf(re)], aff.Qti(t, re, a)));
}
if (a.UseResource(re))
{
col = col.And(model.Column(constraint1[t][aff.RS.IndexOf(re)], 1));
}
}
//第二类约束
col = col.And(model.Column(constraint2[t], 1));
var[t][aff.DS.IndexOf(a)] = model.NumVar(col, 0, double.MaxValue, NumVarType.Float);
}
}
#endregion
return(model);
}
private void InitModel()
{
constraint = model.AddRange(1, 1);
vars = new INumVar[aff.DS.Count];
model.SetOut(null);
//P = new IALPDecision[aff.TimeHorizon];
}
private void InitRMPModel()
{
RMPModel.ClearModel();
cost = RMPModel.AddMaximize();
constraint1 = new IRange[Data.TimeHorizon][];
constraint2 = new IRange[Data.TimeHorizon];
DualValue1 = new double[Data.TimeHorizon][];
DualValue2 = new double[Data.TimeHorizon];
#region //////////////生成约束//////////////
//Parallel.For(0, Data.TimeHorizon, i =>
for (int i = 0; i < Data.TimeHorizon; i++)
{
lock (RMPModel)
{
constraint1[i] = new IRange[Data.RS.Count];
DualValue1[i] = new double[Data.RS.Count];
foreach (IALPResource re in Data.RS)
{
if (i == 0)
{
constraint1[i][Data.RS.IndexOf(re)] = RMPModel.AddRange((Data.InitialState as IALPState)[re], (Data.InitialState as IALPState)[re]);
}
else
{
constraint1[i][Data.RS.IndexOf(re)] = RMPModel.AddRange(0, 0);
}
}
constraint2[i] = RMPModel.AddRange(1, 1);
}
}
#endregion
//RMPModel.SetParam(Cplex.LongParam.RootAlgorithm, 1);
RMPModel.SetOut(SolverTextWriter);
}
public static void Main(string[] args)
{
try {
Cplex cplex = new Cplex();
INumVar[] inside = new INumVar[_nbProds];
INumVar[] outside = new INumVar[_nbProds];
IObjective obj = cplex.AddMinimize();
// Must meet demand for each product
for (int p = 0; p < _nbProds; p++)
{
IRange demRange = cplex.AddRange(_demand[p], _demand[p]);
inside[p] = cplex.NumVar(cplex.Column(obj, _insideCost[p]).And(
cplex.Column(demRange, 1.0)),
0.0, System.Double.MaxValue);
outside[p] = cplex.NumVar(cplex.Column(obj, _outsideCost[p]).And(
cplex.Column(demRange, 1.0)),
0.0, System.Double.MaxValue);
}
// Must respect capacity constraint for each resource
for (int r = 0; r < _nbResources; r++)
{
cplex.AddLe(cplex.ScalProd(_consumption[r], inside), _capacity[r]);
}
cplex.Solve();
if (!cplex.GetStatus().Equals(Cplex.Status.Optimal))
{
System.Console.WriteLine("No optimal solution found");
return;
}
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
DisplayResults(cplex, inside, outside);
System.Console.WriteLine("----------------------------------------");
cplex.End();
}
catch (ILOG.Concert.Exception exc) {
System.Console.WriteLine("Concert exception '" + exc + "' caught");
}
}
public static void Main( string[] args )
{
try {
Cplex cplex = new Cplex();
INumVar[] inside = new INumVar[_nbProds];
INumVar[] outside = new INumVar[_nbProds];
IObjective obj = cplex.AddMinimize();
// Must meet demand for each product
for(int p = 0; p < _nbProds; p++) {
IRange demRange = cplex.AddRange(_demand[p], _demand[p]);
inside[p] = cplex.NumVar(cplex.Column(obj, _insideCost[p]).And(
cplex.Column(demRange, 1.0)),
0.0, System.Double.MaxValue);
outside[p] = cplex.NumVar(cplex.Column(obj, _outsideCost[p]).And(
cplex.Column(demRange, 1.0)),
0.0, System.Double.MaxValue);
}
// Must respect capacity constraint for each resource
for(int r = 0; r < _nbResources; r++)
cplex.AddLe(cplex.ScalProd(_consumption[r], inside), _capacity[r]);
cplex.Solve();
if ( !cplex.GetStatus().Equals(Cplex.Status.Optimal) ) {
System.Console.WriteLine("No optimal solution found");
return;
}
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
DisplayResults(cplex, inside, outside);
System.Console.WriteLine("----------------------------------------");
cplex.End();
}
catch (ILOG.Concert.Exception exc) {
System.Console.WriteLine("Concert exception '" + exc + "' caught");
}
}
public static void Main(string[] args)
{
try {
string datafile = "../../../../examples/data/cutstock.dat";
if (args.Length > 0)
{
datafile = args[0];
}
ReadData(datafile);
/// CUTTING-OPTIMIZATION PROBLEM ///
Cplex cutSolver = new Cplex();
IObjective RollsUsed = cutSolver.AddMinimize();
IRange[] Fill = new IRange[_amount.Length];
for (int f = 0; f < _amount.Length; f++)
{
Fill[f] = cutSolver.AddRange(_amount[f], System.Double.MaxValue);
}
System.Collections.ArrayList Cut = new System.Collections.ArrayList();
int nWdth = _size.Length;
for (int j = 0; j < nWdth; j++)
{
Cut.Add(cutSolver.NumVar(cutSolver.Column(RollsUsed, 1.0).And(
cutSolver.Column(Fill[j],
(int)(_rollWidth / _size[j]))),
0.0, System.Double.MaxValue));
}
cutSolver.SetParam(Cplex.Param.RootAlgorithm, Cplex.Algorithm.Primal);
/// PATTERN-GENERATION PROBLEM ///
Cplex patSolver = new Cplex();
IObjective ReducedCost = patSolver.AddMinimize();
INumVar[] Use = patSolver.NumVarArray(nWdth,
0.0, System.Double.MaxValue,
NumVarType.Int);
patSolver.AddRange(-System.Double.MaxValue,
patSolver.ScalProd(_size, Use),
_rollWidth);
/// COLUMN-GENERATION PROCEDURE ///
double[] newPatt = new double[nWdth];
/// COLUMN-GENERATION PROCEDURE ///
for (;;)
{
/// OPTIMIZE OVER CURRENT PATTERNS ///
cutSolver.Solve();
Report1(cutSolver, Cut, Fill);
/// FIND AND ADD A NEW PATTERN ///
double[] price = cutSolver.GetDuals(Fill);
ReducedCost.Expr = patSolver.Diff(1.0,
patSolver.ScalProd(Use, price));
patSolver.Solve();
Report2(patSolver, Use);
if (patSolver.ObjValue > -RC_EPS)
{
break;
}
newPatt = patSolver.GetValues(Use);
Column column = cutSolver.Column(RollsUsed, 1.0);
for (int p = 0; p < newPatt.Length; p++)
{
column = column.And(cutSolver.Column(Fill[p], newPatt[p]));
}
Cut.Add(cutSolver.NumVar(column, 0.0, System.Double.MaxValue));
}
for (int i = 0; i < Cut.Count; i++)
{
cutSolver.Add(cutSolver.Conversion((INumVar)Cut[i],
NumVarType.Int));
}
cutSolver.Solve();
System.Console.WriteLine("Solution status = " + cutSolver.GetStatus());
Report3(cutSolver, Cut);
cutSolver.End();
patSolver.End();
}
catch (ILOG.Concert.Exception exc) {
System.Console.WriteLine("Concert exception '" + exc + "' caught");
}
catch (System.IO.IOException exc) {
System.Console.WriteLine("Error reading file " + args[0] + ": " + exc);
}
catch (InputDataReader.InputDataReaderException exc) {
System.Console.WriteLine(exc);
}
}
static void Main(string[] args)
{
double[] price = { 170.0, 170.0, 170.0 };
double[] priceStorage = { 10.0, 10.0, 10.0 };
double[] hardness = { 8.4, 6.2, 2.0 };
double[] hardness3 = { 3, 3, 3 };
double[] hardness6 = { 6, 6, 6 };
double[][] oilCost = new double[2][];
oilCost[0] = new double[3] {
1.159550009798596e+02, 1.018115866059220e+02, 1.128780935294160e+02
};
oilCost[1] = new double[3] {
100, 1.067537671189185e+02, 1.098041326934309e+02
};
//oilCost = GenerateRandomVector();
INumVar[][] oilStore = new INumVar[3][];
INumVar[][] oilBuy = new INumVar[2][];
INumVar[][] oilProduce = new INumVar[2][]; // [month][A-C]
Cplex cplex = new Cplex();
for (int i = 0; i < 2; i++) // Initialize oilBuy and oilProduce
{
oilBuy[i] = new INumVar[3];
oilProduce[i] = new INumVar[3];
}
for (int i = 0; i < 3; i++) // Initialize oilStore
{
oilStore[i] = new INumVar[3];
for (int j = 0; j < 3; j++)
{
oilStore[i][j] = cplex.NumVar(0, 800); // Ograniczenia na pojemność magazynu
}
}
for (int i = 0; i < 2; i++) // Ograniczenia na miesiące
{
for (int j = 0; j < 3; j++) // Ograniczenia na możliwości rafinacji
{
if (j != 2)
{
oilProduce[i][j] = cplex.NumVar(0, 220); // Rafinacja roślinnego
}
else
{
oilProduce[i][j] = cplex.NumVar(0, 270); // Rafinacja nie-roślinnego
}
oilBuy[i][j] = cplex.NumVar(0, 1070);
}
cplex.AddRange(0, cplex.Sum(oilProduce[i][0], oilProduce[i][1]), 220);
cplex.AddGe(cplex.ScalProd(hardness, oilProduce[i]), cplex.ScalProd(hardness3, oilProduce[i])); // Hardness greater than 3
cplex.AddLe(cplex.ScalProd(hardness, oilProduce[i]), cplex.ScalProd(hardness6, oilProduce[i])); // Hardness less than 6
}
for (int i = 0; i < 3; i++) // Ograniczenia na oleje
{
cplex.AddEq(oilStore[0][i], 200.0); // Ograniczenie na stan magazynu w grudniu
cplex.AddEq(oilStore[2][i], 200.0); // Ograniczenie na stan magazynu w lutym
cplex.AddEq(oilStore[1][i], cplex.Sum(cplex.Diff(oilBuy[0][i], oilProduce[0][i]), oilStore[0][i])); // (Kupowane + zmagazynowane - produkowane) w tym miesiacu = zmagazynowane w nastepnym miesiacu
cplex.AddEq(oilStore[2][i], cplex.Sum(cplex.Diff(oilBuy[1][i], oilProduce[1][i]), oilStore[1][i]));
}
// Funkcja Celu: zyski ze sprzedaży - koszta magazynowania - koszta kupowania materiału do produkcji
cplex.AddMaximize(
cplex.Diff(
cplex.Diff(
cplex.Sum(
cplex.ScalProd(price, oilProduce[0]),
cplex.ScalProd(price, oilProduce[1])),
cplex.Sum(
cplex.ScalProd(priceStorage, oilStore[1]),
cplex.ScalProd(priceStorage, oilStore[2]))),
cplex.Sum(
cplex.ScalProd(oilCost[0], oilBuy[0]),
cplex.ScalProd(oilCost[1], oilBuy[1]))));
if (cplex.Solve())
{
System.Console.WriteLine();
System.Console.WriteLine("Solution status = " + cplex.GetStatus());
System.Console.WriteLine();
System.Console.WriteLine(" = " + cplex.ObjValue);
Console.WriteLine();
for (int i = 0; i < 2; i++)
{
for (int j = 0; j < 3; j++)
{
Console.WriteLine(" oilCost[" + i + "][" + j + "] = " + oilCost[i][j]);
}
}
Console.WriteLine();
for (int j = 0; j < 2; j++)
{
double hardnessTotal = 0;
double sum = 0;
for (int i = 0; i < 3; i++)
{
System.Console.WriteLine(" oilProduce[" + j + "][" + i + "] = " + cplex.GetValue(oilProduce[j][i]));
hardnessTotal += cplex.GetValue(oilProduce[j][i]) * hardness[i];
sum += cplex.GetValue(oilProduce[j][i]);
}
System.Console.WriteLine(" hardnessTotal[" + j + "] = " + hardnessTotal / sum);
Console.WriteLine();
}
for (int j = 0; j < 2; j++)
{
for (int i = 0; i < 3; i++)
{
System.Console.WriteLine(" oilBuy[" + j + "][" + i + "] = " + cplex.GetValue(oilBuy[j][i]));
}
}
Console.WriteLine();
for (int j = 0; j < 3; j++)
{
for (int i = 0; i < 3; i++)
{
System.Console.WriteLine(" oilStore[" + j + "][" + i + "] = " + cplex.GetValue(oilStore[j][i]));
}
}
System.Console.WriteLine();
}
Console.ReadKey();
}
public static Cplex Build_CD2_Model(IALPFTMDP aff)
{
Cplex model = new Cplex();
IObjective cost = model.AddMaximize();
#region //////////////生成约束//////////////
IRange[][] constraint1 = new IRange[aff.TimeHorizon][];
IRange[][] constraint2 = new IRange[aff.TimeHorizon][];
IRange[] constraint3 = new IRange[aff.TimeHorizon];
for (int i = 0; i < aff.TimeHorizon; i++)
{
constraint1[i] = new IRange[aff.RS.Count];
constraint2[i] = new IRange[aff.RS.Count];
foreach (IALPResource re in aff.RS)
{
if (i == 0)
{
constraint1[i][aff.RS.IndexOf(re)] = model.AddRange((aff.InitialState as IALPState)[re], (aff.InitialState as IALPState)[re]);
constraint2[i][aff.RS.IndexOf(re)] = model.AddRange(double.MinValue, 0);
}
else
{
constraint1[i][aff.RS.IndexOf(re)] = model.AddRange(0, 0);
constraint2[i][aff.RS.IndexOf(re)] = model.AddRange(double.MinValue, 0);
}
}
constraint3[i] = model.AddRange(1, 1);
}
#endregion
#region //////////////生成变量//////////////
//生成h
for (int t = 0; t < aff.TimeHorizon; t++)
{
foreach (IALPDecision a in aff.DS)
{
//目标函数
Column col = model.Column(cost, aff.Rt(t, a));
foreach (IALPResource re in aff.RS)
{
//第一类约束
if (t < aff.TimeHorizon - 1)
{
col = col.And(model.Column(constraint1[t + 1][aff.RS.IndexOf(re)], aff.Qti(t + 1, re, a)));
}
//第二类约束
if (a.UseResource(re))
{
col = col.And(model.Column(constraint2[t][aff.RS.IndexOf(re)], 1));
}
}
//第三类约束
col = col.And(model.Column(constraint3[t], 1));
model.NumVar(col, 0, double.MaxValue, NumVarType.Float);
}
foreach (IALPResource r in aff.RS)
{
Column col = model.Column(cost, 0);// cost, aff.Rt(t, a));
if (t < aff.TimeHorizon - 1)
{
col = col.And(model.Column(constraint1[t + 1][aff.RS.IndexOf(r)], -1));
}
col = col.And(model.Column(constraint1[t][aff.RS.IndexOf(r)], 1));
col = col.And(model.Column(constraint2[t][aff.RS.IndexOf(r)], -1));
model.NumVar(col, 0, double.MaxValue, NumVarType.Float);
}
}
///);
#endregion
return(model);
}
//Piece-Wise Function Approximation
public static Cplex Build_Dual_PW_Model(IALPFTMDP aff)
{
Cplex model = new Cplex();
IObjective cost = model.AddMaximize();
#region //////////////生成约束//////////////
IRange[][][] constraint1 = new IRange[aff.TimeHorizon][][];
IRange[] constraint2 = new IRange[aff.TimeHorizon];
for (int i = 0; i < aff.TimeHorizon; i++)
{
constraint1[i] = new IRange[aff.RS.Count][];
foreach (IALPResource re in aff.RS)
{
constraint1[i][aff.RS.IndexOf(re)] = new IRange[(aff.InitialState as IALPState)[re]];
for (int k = 1; k < (aff.InitialState as IALPState)[re]; k++)
{
if (i == 0)
{
constraint1[i][aff.RS.IndexOf(re)][k - 1] = model.AddRange(1, 1);
}
else
{
constraint1[i][aff.RS.IndexOf(re)][k - 1] = model.AddRange(0, 0);
}
}
}
constraint2[i] = model.AddRange(1, 1);
}
#endregion
#region //////////////生成变量//////////////
//System.Threading.Tasks.Parallel.For(0, aff.TimeHorizon, (t) =>
for (int t = 0; t < aff.TimeHorizon; t++)
{
foreach (IALPState s in aff.SS)
{
foreach (IMDPDecision a in aff.GenDecisionSpace(s))
{
//目标函数
Column col = model.Column(cost, aff.Reward(t, s, a));
// System.Console.WriteLine(aff.Reward(t, s, a));
//第一类约束
foreach (IALPResource re in aff.RS)
{
for (int k = 1; k < (aff.InitialState as IALPState)[re]; k++)
{
if (s[re] >= k)
{
col = col.And(model.Column(constraint1[t][aff.RS.IndexOf(re)][k - 1], 1));
if (t < aff.TimeHorizon - 1)
{
col = col.And(model.Column(constraint1[t + 1][aff.RS.IndexOf(re)][k - 1], -1));
if (s[re] == k)
{
col = col.And(model.Column(constraint1[t + 1][aff.RS.IndexOf(re)][k - 1], (aff.Qti(t, re, a))));
}
}
}
}
}
//第二类约束
col = col.And(model.Column(constraint2[t], 1));
model.NumVar(col, 0, double.MaxValue, NumVarType.Float);
}
}
}
///);
#endregion
model.SetOut(null);
return(model);
}
public static void Main( string[] args )
{
try {
string datafile = "../../../../examples/data/cutstock.dat";
if (args.Length > 0)
datafile = args[0];
ReadData(datafile);
/// CUTTING-OPTIMIZATION PROBLEM ///
Cplex cutSolver = new Cplex();
IObjective RollsUsed = cutSolver.AddMinimize();
IRange[] Fill = new IRange[_amount.Length];
for (int f = 0; f < _amount.Length; f++ ) {
Fill[f] = cutSolver.AddRange(_amount[f], System.Double.MaxValue);
}
System.Collections.ArrayList Cut = new System.Collections.ArrayList();
int nWdth = _size.Length;
for (int j = 0; j < nWdth; j++)
Cut.Add(cutSolver.NumVar(cutSolver.Column(RollsUsed, 1.0).And(
cutSolver.Column(Fill[j],
(int)(_rollWidth/_size[j]))),
0.0, System.Double.MaxValue));
cutSolver.SetParam(Cplex.Param.RootAlgorithm, Cplex.Algorithm.Primal);
/// PATTERN-GENERATION PROBLEM ///
Cplex patSolver = new Cplex();
IObjective ReducedCost = patSolver.AddMinimize();
INumVar[] Use = patSolver.NumVarArray(nWdth,
0.0, System.Double.MaxValue,
NumVarType.Int);
patSolver.AddRange(-System.Double.MaxValue,
patSolver.ScalProd(_size, Use),
_rollWidth);
/// COLUMN-GENERATION PROCEDURE ///
double[] newPatt = new double[nWdth];
/// COLUMN-GENERATION PROCEDURE ///
for (;;) {
/// OPTIMIZE OVER CURRENT PATTERNS ///
cutSolver.Solve();
Report1(cutSolver, Cut, Fill);
/// FIND AND ADD A NEW PATTERN ///
double[] price = cutSolver.GetDuals(Fill);
ReducedCost.Expr = patSolver.Diff(1.0,
patSolver.ScalProd(Use, price));
patSolver.Solve();
Report2 (patSolver, Use);
if ( patSolver.ObjValue > -RC_EPS )
break;
newPatt = patSolver.GetValues(Use);
Column column = cutSolver.Column(RollsUsed, 1.0);
for ( int p = 0; p < newPatt.Length; p++ )
column = column.And(cutSolver.Column(Fill[p], newPatt[p]));
Cut.Add( cutSolver.NumVar(column, 0.0, System.Double.MaxValue) );
}
for ( int i = 0; i < Cut.Count; i++ ) {
cutSolver.Add(cutSolver.Conversion((INumVar)Cut[i],
NumVarType.Int));
}
cutSolver.Solve();
System.Console.WriteLine("Solution status = " + cutSolver.GetStatus());
Report3 (cutSolver, Cut);
cutSolver.End();
patSolver.End();
}
catch ( ILOG.Concert.Exception exc ) {
System.Console.WriteLine("Concert exception '" + exc + "' caught");
}
catch (System.IO.IOException exc) {
System.Console.WriteLine("Error reading file " + args[0] + ": " + exc);
}
catch (InputDataReader.InputDataReaderException exc ) {
System.Console.WriteLine(exc);
}
}
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");
}
}
static void Main(string[] args)
{
double BinCap = 0;
var dict = InputReader.ReadDataFile(ref BinCap);
Cplex cplex = new Cplex();
Dictionary <string, INumVar> dictvariables = new Dictionary <string, INumVar>();
Dictionary <string, IRange> dictconstraints = new Dictionary <string, IRange>();
IObjective objective = cplex.AddMinimize();
foreach (var vari in dict.Keys)
{
var cname = "C" + vari;
dictconstraints.Add(cname, cplex.AddRange(1, Int32.MaxValue, cname));
}
Dictionary <int, Set> InitialSets = new Dictionary <int, Set>();;
InitialSets.Add(1, new Set(new List <int> {
1, 5
}));
InitialSets.Add(2, new Set(new List <int> {
2, 5
}));
InitialSets.Add(3, new Set(new List <int> {
3, 5
}));
InitialSets.Add(4, new Set(new List <int> {
4, 5
}));
//Add intial sets to the model
foreach (var vari in InitialSets)
{
var setID = vari.Key.ToString();
Column VarSet = cplex.Column(objective, 1);
foreach (var members in vari.Value.member)
{
var cname = "C" + members;
VarSet = VarSet.And(cplex.Column(dictconstraints[cname], 1));
}
dictvariables.Add(setID, cplex.NumVar(VarSet, 0, 1, NumVarType.Float));
}
cplex.Solve();
var duals = getDuals(cplex, dictconstraints);
var solution = getSolution(cplex, dictvariables);
Console.WriteLine("The objective value is {0}", cplex.GetObjValue());
int piter = 0;
int fixediter = 0;
Dictionary <string, INumVar> Fixedvar = new Dictionary <string, INumVar>();
while (true)
{
//Formulate Pricing Problem
Cplex pcplex = new Cplex();
IObjective pobjective = pcplex.AddMaximize();
piter++;
//Add Bin Capacity Constraint
IRange Knapsack = pcplex.AddRange(0, BinCap, "Bin");
Dictionary <string, INumVar> pdictvar = new Dictionary <string, INumVar>();
foreach (var vari in dict.Keys)
{
var varname = vari.ToString();
var objcoeff = duals["C" + varname];
Column item = pcplex.Column(pobjective, objcoeff);
item = item.And(pcplex.Column(Knapsack, dict[vari]));
pdictvar.Add(varname, pcplex.NumVar(item, 0, 1, NumVarType.Int));
}
pcplex.Solve();
if (pcplex.GetObjValue() > 1)
{
Console.WriteLine("Pricing Iteration: {0} and obj value is {1} ", piter, pcplex.GetObjValue());
var psolution = getSolution(pcplex, pdictvar);
List <int> sol = new List <int>();
foreach (var vari in psolution.Keys)
{
sol.Add(Convert.ToInt32(vari));
}
InitialSets.Add(InitialSets.Count + 1, new Set(sol));
var setID = (InitialSets.Count).ToString();
Column VarSet1 = cplex.Column(objective, 1);
foreach (var members in sol)
{
var cname = "C" + members;
VarSet1 = VarSet1.And(cplex.Column(dictconstraints[cname], 1));
}
dictvariables.Add(setID, cplex.NumVar(VarSet1, 0, 1, NumVarType.Float));
cplex.Solve();
Console.WriteLine("The objective value of cplex after adding column is {0}", cplex.GetObjValue());
duals = getDuals(cplex, dictconstraints);
solution = getSolution(cplex, dictvariables);
}
else
{
fixediter++;
bool fixedsomething = false;
//fix variables above 0.5
foreach (var val in solution)
{
if (val.Value > 0.5 && !Fixedvar.ContainsKey(val.Key))
{
Fixedvar.Add(val.Key, dictvariables[val.Key]);
dictvariables[val.Key].LB = 1;
fixedsomething = true;
}
}
if (!fixedsomething)
{
break;
}
cplex.Solve();
Console.WriteLine("The Fixing iterations is {0}", cplex.GetObjValue());
duals = getDuals(cplex, dictconstraints);
}
}
foreach (var vari in Fixedvar.Values)
{
vari.LB = 0;
}
IConversion IP = cplex.Conversion(dictvariables.Values.ToArray(), NumVarType.Int);
cplex.Add(IP);
cplex.SetParam(Cplex.DoubleParam.TiLim, 600);
cplex.Solve();
solution = getSolution(cplex, dictvariables);
Console.WriteLine("The objective value is {0}", cplex.GetObjValue());
}
