public double SolveBasic(int branchLimit)
{
// Objective
Console.WriteLine();
Console.WriteLine(" ! ----------------------------------------------------------------------------");
Console.WriteLine(" ! Minimizing total cost");
Console.WriteLine(" ! ----------------------------------------------------------------------------");
IIntExpr costExpr = cp.IntExpr();
int nbMachines = machines.Length;
int nbJobs = machines[0].Length;
for (int i = 0; i < nbJobs; i++)
{
for (int j = 0; j < nbMachines; j++)
{
costExpr = cp.Sum(costExpr, cp.Prod(costs[j][i], cp.PresenceOf(machines[j][i])));
}
}
IObjective obj = cp.Minimize(costExpr);
cp.Add(obj);
cp.SetParameter(CP.IntParam.LogPeriod, 600000);
cp.SetParameter(CP.IntParam.BranchLimit, branchLimit);
cp.SetParameter(CP.IntParam.NoOverlapInferenceLevel, CP.ParameterValues.Extended);
cp.Solve();
double cost = cp.ObjValue;
return(cost);
}
private Cplex initCplex(VariabilityModel vm)
{
Cplex cplex = new Cplex();
one = cplex.Constant(1);
initializeBinaryVariables(cplex, vm);
return(cplex);
}
private void BuildModel()
{
// Create the decision variables, cost, and the model
scene = new IIntVar[numScenes];
for (int s = 0; s < numScenes; s++)
{
scene[s] = cp.IntVar(0, numScenes - 1);
}
// Expression representing the global cost
idleCost = cp.IntExpr();
// Make the slot-based secondary model
IIntVar[] slot = new IIntVar[numScenes];
for (int s = 0; s < numScenes; s++)
{
slot[s] = cp.IntVar(0, numScenes - 1);
}
cp.Add(cp.Inverse(scene, slot));
// Loop over all actors, building cost
for (int a = 0; a < numActors; a++)
{
// Expression for the waiting time for this actor
IIntExpr actorWait = cp.IntExpr();
// Calculate the first and last slots where this actor plays
List <IIntVar> position = new List <IIntVar>();
System.Collections.IEnumerator en = actorInScene[a].GetEnumerator();
while (en.MoveNext())
{
position.Add(slot[(int)en.Current]);
}
IIntExpr firstSlot = cp.Min(position.ToArray());
IIntExpr lastSlot = cp.Max(position.ToArray());
// If an actor is not in a scene, he waits
// if he is on set when the scene is filmed
for (int s = 0; s < numScenes; s++)
{
if (!actorInScene[a].Contains(s))
{ // not in scene
IIntExpr wait = cp.And(cp.Le(firstSlot, slot[s]), cp.Le(
slot[s], lastSlot));
actorWait = cp.Sum(actorWait, cp.Prod(sceneDuration[s],
wait));
}
}
// Accumulate the cost of waiting time for this actor
idleCost = cp.Sum(idleCost, cp.Prod(actorPay[a], actorWait));
}
cp.Add(cp.Minimize(idleCost));
}
public static IIntExpr MakeScenarioSubmodel(CP cp,
int nbJobs,
int nbMachines,
int[][] machines,
int[][] durations,
IIntervalSequenceVar[] sequences)
{
List <IIntervalVar>[] machinesOps = new List <IIntervalVar> [nbMachines];
String name;
int i, j;
for (j = 0; j < nbMachines; j++)
{
machinesOps[j] = new List <IIntervalVar>();
}
IIntExpr[] ends = new IIntExpr[nbJobs];
for (i = 0; i < nbJobs; i++)
{
IIntervalVar prec = cp.IntervalVar();
for (j = 0; j < nbMachines; j++)
{
name = "J" + i + "_O" + j;
IIntervalVar ti = cp.IntervalVar(durations[i][j], name);
machinesOps[machines[i][j]].Add(ti);
if (j > 0)
{
cp.Add(cp.EndBeforeStart(prec, ti));
}
prec = ti;
}
ends[i] = cp.EndOf(prec);
}
for (j = 0; j < nbMachines; j++)
{
name = "M" + j;
sequences[j] = cp.IntervalSequenceVar(machinesOps[j].ToArray(), name);
cp.Add(cp.NoOverlap(sequences[j]));
}
return(cp.Max(ends));
}
static void Main(string[] args)
{
CP cp = new CP();
int weightSum = 0;
for (int o = 0; o < nbOrders; o++)
{
weightSum += weight[o];
}
IIntVar[] where = new IIntVar[nbOrders];
for (int o = 0; o < nbOrders; o++)
{
where[o] = cp.IntVar(0, nbSlabs - 1);
}
IIntVar[] load = new IIntVar[nbSlabs];
for (int m = 0; m < nbSlabs; m++)
{
load[m] = cp.IntVar(0, weightSum);
}
// Pack constraint
cp.Add(cp.Pack(load, where, weight));
// Color constraints
for (int m = 0; m < nbSlabs; m++)
{
IIntExpr[] colorExpArray = new IIntExpr[nbColors];
for (int c = 0; c < nbColors; c++)
{
IConstraint orCt = cp.FalseConstraint();
for (int o = 0; o < nbOrders; o++)
{
if (colors[o] == c)
{
orCt = cp.Or(orCt, cp.Eq(where[o], m));
}
}
colorExpArray[c] = cp.IntExpr(orCt);
}
cp.Add(cp.Le(cp.Sum(colorExpArray), 2));
}
// Objective function
int sizeLossValues = capacities[capacities.Length - 1] - capacities[0] + 1;
int[] lossValues = new int[sizeLossValues];
lossValues[0] = 0;
int indexValue = 1;
for (int q = 1; q < capacities.Length; q++)
{
for (int p = capacities[q - 1] + 1; p <= capacities[q]; p++)
{
lossValues[indexValue] = capacities[q] - p;
indexValue++;
}
}
IIntExpr obj = cp.Constant(0);
for (int m = 0; m < nbSlabs; m++)
{
obj = cp.Sum(obj, cp.Element(lossValues, load[m]));
}
cp.Add(cp.Minimize(obj));
// - A symmetry breaking constraint that is useful for small instances
for (int m = 1; m < nbSlabs; m++)
{
cp.Add(cp.Ge(load[m - 1], load[m]));
}
if (cp.Solve())
{
Console.WriteLine("Optimal value: " + cp.GetValue(obj));
for (int m = 0; m < nbSlabs; m++)
{
int p = 0;
for (int o = 0; o < nbOrders; o++)
{
if (cp.GetValue(where[o]) == m)
{
++p;
}
}
if (p == 0)
{
continue;
}
Console.Write("Slab " + m + " is used for order");
if (p > 1)
{
Console.Write("s");
}
Console.Write(" :");
for (int o = 0; o < nbOrders; o++)
{
if (cp.GetValue(where[o]) == m)
{
Console.Write(" " + o);
}
}
Console.WriteLine();
}
}
}
static void Main(string[] args)
{
String filename;
if (args.Length > 0)
{
filename = args[0];
}
else
{
filename = "../../../../examples/data/facility.data";
}
CP cp = new CP();
int i, j;
DataReader data = new DataReader(filename);
int nbLocations = data.Next();
int nbStores = data.Next();
int[] capacity = new int[nbLocations];
int[] fixedCost = new int[nbLocations];
int[][] cost = new int[nbStores][];
for (i = 0; i < nbStores; i++)
{
cost[i] = new int[nbLocations];
}
for (j = 0; j < nbLocations; j++)
{
capacity[j] = data.Next();
}
for (j = 0; j < nbLocations; j++)
{
fixedCost[j] = data.Next();
}
for (i = 0; i < nbStores; i++)
{
for (j = 0; j < nbLocations; j++)
{
cost[i][j] = data.Next();
}
}
IIntVar[] supplier = cp.IntVarArray(nbStores, 0, nbLocations - 1);
IIntVar[] open = cp.IntVarArray(nbLocations, 0, 1);
for (i = 0; i < nbStores; i++)
{
cp.Add(cp.Eq(cp.Element(open, supplier[i]), 1));
}
for (j = 0; j < nbLocations; j++)
{
cp.Add(cp.Le(cp.Count(supplier, j), capacity[j]));
}
IIntExpr obj = cp.ScalProd(open, fixedCost);
for (i = 0; i < nbStores; i++)
{
obj = cp.Sum(obj, cp.Element(cost[i], supplier[i]));
}
cp.Add(cp.Minimize(obj));
cp.SetParameter(CP.IntParam.Workers, 1);
cp.SetParameter(CP.IntParam.SearchType, CP.ParameterValues.DepthFirst);
cp.SetParameter(CP.IntParam.LogPeriod, 1);
cp.SetParameter(CP.IntParam.LogSearchTags, CP.ParameterValues.On);
cp.Solve();
cp.ClearExplanations();
cp.ExplainFailure(15);
cp.ExplainFailure(20);
int[] failureArray = { 3, 10, 11, 12 };
cp.ExplainFailure(failureArray);
cp.Solve();
cp.ClearExplanations();
cp.ExplainFailure(1);
cp.Solve();
Console.WriteLine();
Console.WriteLine("Optimal value: " + cp.GetValue(obj));
for (j = 0; j < nbLocations; j++)
{
if (cp.GetValue(open[j]) == 1)
{
Console.Write("Facility " + j + " is open, it serves stores ");
for (i = 0; i < nbStores; i++)
{
if (cp.GetValue(supplier[i]) == j)
{
Console.Write(i + " ");
}
}
Console.WriteLine();
}
}
}
public static void Main(String[] args)
{
try
{
CP cp = new CP();
ITransitionDistance setup1 = cp.TransitionDistance(NbTypes);
ITransitionDistance setup2 = cp.TransitionDistance(NbTypes);
int i, j;
for (i = 0; i < NbTypes; ++i)
{
for (j = 0; j < NbTypes; ++j)
{
int d1 = SetupM1[NbTypes * i + j];
if (d1 < 0)
d1 = CP.IntervalMax; // Forbidden transition
setup1.SetValue(i, j, d1);
int d2 = SetupM2[NbTypes * i + j];
if (d2 < 0)
d2 = CP.IntervalMax; // Forbidden transition
setup2.SetValue(i, j, d2);
}
}
int[] tp = new int[NbTasks];
IIntervalVar[] a = new IIntervalVar[NbTasks];
IIntervalVar[] a1 = new IIntervalVar[NbTasks];
IIntervalVar[] a2 = new IIntervalVar[NbTasks];
IIntExpr[] ends = new IIntExpr[NbTasks];
String name;
for (i = 0; i < NbTasks; ++i)
{
int type = TaskType[i];
int d1 = TaskDurM1[i];
int d2 = TaskDurM2[i];
tp[i] = type;
name = "A" + i + "_TP" + type;
a[i] = cp.IntervalVar(name);
IIntervalVar[] alt = new IIntervalVar[2];
name = "A" + i + "_M1_TP" + type;
a1[i] = cp.IntervalVar(d1, name);
a1[i].SetOptional();
alt[0] = a1[i];
name = "A" + i + "_M2_TP" + type;
a2[i] = cp.IntervalVar(d2, name);
a2[i].SetOptional();
alt[1] = a2[i];
cp.Add(cp.Alternative(a[i], alt));
ends[i] = cp.EndOf(a[i]);
}
IIntervalSequenceVar s1 = cp.IntervalSequenceVar(a1, tp);
IIntervalSequenceVar s2 = cp.IntervalSequenceVar(a2, tp);
cp.Add(cp.NoOverlap(s1, setup1, true));
cp.Add(cp.NoOverlap(s2, setup2, true));
cp.Add(cp.Minimize(cp.Max(ends)));
cp.SetParameter(CP.IntParam.FailLimit, 100000);
cp.SetParameter(CP.IntParam.LogPeriod, 10000);
if (cp.Solve())
{
Console.WriteLine("Machine 1: ");
IIntervalVar x;
for (x = cp.GetFirst(s1); !x.Equals(cp.GetLast(s1)); x = cp.GetNext(s1, x))
Console.WriteLine(cp.GetDomain(x));
Console.WriteLine(cp.GetDomain(x));
Console.WriteLine("Machine 2: ");
for (x = cp.GetFirst(s2); !x.Equals(cp.GetLast(s2)); x = cp.GetNext(s2, x))
Console.WriteLine(cp.GetDomain(x));
Console.WriteLine(cp.GetDomain(x));
Console.WriteLine("Makespan \t: " + cp.ObjValue);
}
else
{
Console.WriteLine("No solution found.");
}
}
catch (IloException e)
{
Console.WriteLine("Error: " + e);
}
}
static void Main(string[] args)
{
CP cp = new CP();
int weightSum=0;
for (int o = 0; o < nbOrders; o++)
weightSum += weight[o];
IIntVar[] where = new IIntVar[nbOrders];
for(int o = 0; o < nbOrders; o++)
where[o] = cp.IntVar(0, nbSlabs-1);
IIntVar[] load = new IIntVar[nbSlabs];
for(int m = 0; m < nbSlabs; m++)
load[m] = cp.IntVar(0, weightSum);
// Pack constraint
cp.Add(cp.Pack(load, where, weight));
// Color constraints
for(int m = 0; m < nbSlabs; m++) {
IIntExpr[] colorExpArray = new IIntExpr[nbColors];
for(int c = 0; c < nbColors; c++) {
IConstraint orCt = cp.FalseConstraint();
for(int o = 0; o < nbOrders; o++){
if (colors[o] == c){
orCt = cp.Or(orCt, cp.Eq(where[o], m));
}
}
colorExpArray[c] = cp.IntExpr(orCt);
}
cp.Add(cp.Le(cp.Sum(colorExpArray), 2));
}
// Objective function
int sizeLossValues = capacities[capacities.Length-1] - capacities[0] + 1;
int[] lossValues = new int[sizeLossValues];
lossValues[0]= 0;
int indexValue= 1;
for(int q = 1; q < capacities.Length; q++){
for(int p = capacities[q-1] + 1; p <= capacities[q]; p++){
lossValues[indexValue] = capacities[q] - p;
indexValue++;
}
}
IIntExpr obj = cp.Constant(0);
for(int m = 0; m < nbSlabs; m++){
obj = cp.Sum(obj, cp.Element(lossValues, load[m]));
}
cp.Add(cp.Minimize(obj));
// - A symmetry breaking constraint that is useful for small instances
for(int m = 1; m < nbSlabs; m++){
cp.Add(cp.Ge(load[m-1],load[m]));
}
if (cp.Solve()){
Console.WriteLine("Optimal value: " + cp.GetValue(obj));
for (int m = 0; m < nbSlabs; m++) {
int p = 0;
for (int o = 0; o < nbOrders; o++)
if (cp.GetValue(where[o]) == m) ++p;
if (p == 0) continue;
Console.Write("Slab " + m + " is used for order");
if (p > 1) Console.Write("s");
Console.Write(" :");
for (int o = 0; o < nbOrders; o++) {
if (cp.GetValue(where[o]) == m)
Console.Write(" " + o);
}
Console.WriteLine();
}
}
}
static void Main(string[] args)
{
String filename;
if (args.Length > 0)
{
filename = args[0];
}
else
{
filename = "../../../../examples/data/facility.data";
}
CP cp = new CP();
int i, j;
DataReader data = new DataReader(filename);
int nbLocations = data.Next();
int nbStores = data.Next();
int[] capacity = new int[nbLocations];
int[] fixedCost = new int[nbLocations];
int[][] cost = new int[nbStores][];
for (i = 0; i < nbStores; i++)
{
cost[i] = new int[nbLocations];
}
for (j = 0; j < nbLocations; j++)
{
capacity[j] = data.Next();
}
for (j = 0; j < nbLocations; j++)
{
fixedCost[j] = data.Next();
}
for (i = 0; i < nbStores; i++)
{
for (j = 0; j < nbLocations; j++)
{
cost[i][j] = data.Next();
}
}
IIntVar[] supplier = cp.IntVarArray(nbStores, 0, nbLocations - 1);
IIntVar[] open = cp.IntVarArray(nbLocations, 0, 1);
for (i = 0; i < nbStores; i++)
{
cp.Add(cp.Eq(cp.Element(open, supplier[i]), 1));
}
for (j = 0; j < nbLocations; j++)
{
cp.Add(cp.Le(cp.Count(supplier, j), capacity[j]));
}
IIntExpr obj = cp.ScalProd(open, fixedCost);
for (i = 0; i < nbStores; i++)
{
obj = cp.Sum(obj, cp.Element(cost[i], supplier[i]));
}
cp.Add(cp.Minimize(obj));
cp.Solve();
Console.WriteLine();
Console.WriteLine("Optimal value: " + cp.GetValue(obj));
for (j = 0; j < nbLocations; j++)
{
if (cp.GetValue(open[j]) == 1)
{
Console.Write("Facility " + j + " is open, it serves stores ");
for (i = 0; i < nbStores; i++)
{
if (cp.GetValue(supplier[i]) == j)
{
Console.Write(i + " ");
}
}
Console.WriteLine();
}
}
}
public static void Main(String[] args)
{
String filename = "../../../../examples/data/rcpspmm_default.data";
int failLimit = 30000;
int nbTasks, nbRenewable, nbNonRenewable;
if (args.Length > 0)
{
filename = args[0];
}
if (args.Length > 1)
{
failLimit = Convert.ToInt32(args[1]);
}
CP cp = new CP();
DataReader data = new DataReader(filename);
nbTasks = data.Next();
nbRenewable = data.Next();
nbNonRenewable = data.Next();
ICumulFunctionExpr[] renewables = new ICumulFunctionExpr[nbRenewable];
IIntExpr[] nonRenewables = new IIntExpr[nbNonRenewable];
int[] capRenewables = new int[nbRenewable];
int[] capNonRenewables = new int[nbNonRenewable];
for (int j = 0; j < nbRenewable; j++)
{
renewables[j] = cp.CumulFunctionExpr();
capRenewables[j] = data.Next();
}
for (int j = 0; j < nbNonRenewable; j++)
{
nonRenewables[j] = cp.IntExpr();
capNonRenewables[j] = data.Next();
}
IIntervalVar[] tasks = new IIntervalVar[nbTasks];
List <IIntervalVar>[] modes = new List <IIntervalVar> [nbTasks];
for (int i = 0; i < nbTasks; i++)
{
tasks[i] = cp.IntervalVar();
modes[i] = new List <IIntervalVar>();
}
List <IIntExpr> ends = new List <IIntExpr>();
for (int i = 0; i < nbTasks; i++)
{
IIntervalVar task = tasks[i];
int d = data.Next();
int nbModes = data.Next();
int nbSucc = data.Next();
for (int k = 0; k < nbModes; k++)
{
IIntervalVar alt = cp.IntervalVar();
alt.SetOptional();
modes[i].Add(alt);
}
cp.Add(cp.Alternative(task, modes[i].ToArray()));
ends.Add(cp.EndOf(task));
for (int s = 0; s < nbSucc; s++)
{
int succ = data.Next();
cp.Add(cp.EndBeforeStart(task, tasks[succ]));
}
}
for (int i = 0; i < nbTasks; i++)
{
IIntervalVar task = tasks[i];
List <IIntervalVar> imodes = modes[i];
for (int k = 0; k < imodes.Count; k++)
{
int taskId = data.Next();
int modeId = data.Next();
int d = data.Next();
imodes[k].SizeMin = d;
imodes[k].SizeMax = d;
int q;
for (int j = 0; j < nbNonRenewable; j++)
{
q = data.Next();
if (0 < q)
{
renewables[j].Add(cp.Pulse(imodes[k], q));
}
}
for (int j = 0; j < nbNonRenewable; j++)
{
q = data.Next();
if (0 < q)
{
nonRenewables[j] = cp.Sum(nonRenewables[j], cp.Prod(q, cp.PresenceOf(imodes[k])));
}
}
}
}
for (int j = 0; j < nbRenewable; j++)
{
cp.Add(cp.Le(renewables[j], capRenewables[j]));
}
for (int j = 0; j < nbRenewable; j++)
{
cp.Add(cp.Le(nonRenewables[j], capNonRenewables[j]));
}
IObjective objective = cp.Minimize(cp.Max(ends.ToArray()));
cp.Add(objective);
cp.SetParameter(CP.IntParam.FailLimit, failLimit);
Console.WriteLine("Instance \t: " + filename);
if (cp.Solve())
{
Console.WriteLine("Makespan \t: " + cp.ObjValue);
}
else
{
Console.WriteLine("No solution found.");
}
}
public static void Main(String[] args)
{
String filename = "../../../../examples/data/learningeffect_default.data";
int failLimit = 10000;
int nbJobs, nbMachines;
if (args.Length > 0)
filename = args[0];
if (args.Length > 1)
failLimit = Convert.ToInt32(args[1]);
CP cp = new CP();
DataReader data = new DataReader(filename);
nbJobs = data.Next();
nbMachines = data.Next();
IIntExpr[] ends = new IIntExpr[nbJobs];
IIntervalVar[][] machines = new IIntervalVar[nbMachines][];
int[][] sizes = new int[nbMachines][];
for (int j = 0; j < nbMachines; j++) {
machines[j] = new IIntervalVar[nbJobs];
sizes[j] = new int[nbJobs];
}
for (int i = 0; i < nbJobs; i++)
{
IIntervalVar prec = cp.IntervalVar();
for (int j = 0; j < nbMachines; j++)
{
int m, d;
m = data.Next();
d = data.Next();
IIntervalVar ti = cp.IntervalVar(0, d);
machines[m][i] = ti;
sizes[m][i] = d;
if (j > 0)
{
cp.Add(cp.EndBeforeStart(prec, ti));
}
prec = ti;
}
ends[i] = cp.EndOf(prec);
}
for (int j = 0; j < nbMachines; j++)
{
double alpha = data.Next() / ((double) 100);
IIntervalVar[] chain = new IIntervalVar[nbJobs];
IIntervalVar prec = cp.IntervalVar();
IIntExpr[] indices = new IIntExpr[nbJobs];
for (int i = 0; i < nbJobs; i++) {
IIntervalVar syncti = cp.IntervalVar();
if (i > 0)
{
cp.Add(cp.EndBeforeStart(prec, syncti));
}
prec = syncti;
chain[i] = syncti;
IIntExpr index = cp.IntVar(0, nbJobs -1);
indices[i] = index;
// Learning effect captured by the decreasing function
// of the position (0 <= alpha <= 1).
// At first position, in the sequence index = 0; there is no
// learning effect and duration of the task is its nominal duration
cp.Add(cp.Eq(cp.SizeOf(machines[j][i]),
cp.Floor(cp.Prod(sizes[j][i],
cp.Power(alpha, index)))));
}
cp.Add(cp.Isomorphism(chain, machines[j], indices, nbJobs));
// The no-overlap is a redundant constraint in this quite
// simple model - it is used only to provide stronger inference.
cp.Add(cp.NoOverlap(machines[j]));
}
IObjective objective = cp.Minimize(cp.Max(ends));
cp.Add(objective);
cp.SetParameter(CP.IntParam.FailLimit, failLimit);
Console.WriteLine("Instance \t: " + filename);
if (cp.Solve())
{
Console.WriteLine("Makespan \t: " + cp.ObjValue);
}
else
{
Console.WriteLine("No solution found.");
}
}
public static void Main(String[] args)
{
String filename = "../../../../examples/data/stochastic_jobshop_default.data";
int failLimit = 250000;
if (args.Length > 0)
{
filename = args[0];
}
if (args.Length > 1)
{
failLimit = Convert.ToInt32(args[1]);
}
// Data reading
DataReader data = new DataReader(filename);
int nbJobs, nbMachines, nbScenarios;
nbJobs = data.Next();
nbMachines = data.Next();
nbScenarios = data.Next();
int i, j, k;
// machines[i][j]: machine used by jth operation of job i
int[][] machines = new int[nbJobs][];
for (i = 0; i < nbJobs; i++)
{
machines[i] = new int[nbMachines];
for (j = 0; j < nbMachines; j++)
{
machines[i][j] = data.Next();
}
}
// durations[k][i][j]: duration of jth operation of job i in scenario k
int[][][] durations = new int[nbScenarios][][];
for (k = 0; k < nbScenarios; k++)
{
durations[k] = new int[nbJobs][];
for (i = 0; i < nbJobs; i++)
{
durations[k][i] = new int[nbMachines];
for (j = 0; j < nbMachines; j++)
{
durations[k][i][j] = data.Next();
}
}
}
CP cp = new CP();
IIntervalSequenceVar[] refSequences = new IIntervalSequenceVar[nbMachines];
IIntExpr sumMakespan = cp.IntExpr();
for (k = 0; k < nbScenarios; k++)
{
IIntervalSequenceVar[] scenarioSequences = new IIntervalSequenceVar[nbMachines];
IIntExpr scenarioMakespan =
MakeScenarioSubmodel(cp, nbJobs, nbMachines,
machines, durations[k],
scenarioSequences);
// Objective function is aggregated
sumMakespan = cp.Sum(sumMakespan, scenarioMakespan);
// For each machine, a sameSequence constraint is posted across all scenarios
if (0 == k)
{
refSequences = scenarioSequences;
}
else
{
for (j = 0; j < nbMachines; j++)
{
cp.Add(cp.SameSequence(refSequences[j], scenarioSequences[j]));
}
}
}
// Objective function is expected makespan
INumExpr expectedMakespan = cp.Quot(sumMakespan, nbScenarios);
IObjective objective = cp.Minimize(expectedMakespan);
cp.Add(objective);
cp.SetParameter(CP.IntParam.FailLimit, failLimit);
cp.SetParameter(CP.IntParam.LogPeriod, 1000000);
Console.WriteLine("Instance \t: " + filename);
if (cp.Solve())
{
Console.WriteLine("Expected makespan \t: " + cp.ObjValue);
for (j = 0; j < nbMachines; ++j)
{
IIntervalSequenceVar s = refSequences[j];
Console.Write(s.Name + ":\t");
IIntervalVar op = cp.GetFirst(s);
for (; !op.Equals(cp.GetLast(s)); op = cp.GetNext(s, op))
{
Console.Write(op.Name + "\t");
}
Console.WriteLine(op.Name + "\t");
}
}
else
{
Console.WriteLine("No solution found.");
}
}
public static void Main(String[] args)
{
try
{
CP cp = new CP();
ITransitionDistance setup1 = cp.TransitionDistance(NbTypes);
ITransitionDistance setup2 = cp.TransitionDistance(NbTypes);
int i, j;
for (i = 0; i < NbTypes; ++i)
{
for (j = 0; j < NbTypes; ++j)
{
setup1.SetValue(i, j, SetupM1[NbTypes * i + j]);
setup2.SetValue(i, j, SetupM2[NbTypes * i + j]);
}
}
int[] tp = new int[NbTasks];
IIntervalVar[] a = new IIntervalVar[NbTasks];
IIntervalVar[] a1 = new IIntervalVar[NbTasks];
IIntervalVar[] a2 = new IIntervalVar[NbTasks];
String name;
for (i = 0; i < NbTasks; ++i)
{
int type = TaskType[i];
int d = TaskDur[i];
tp[i] = type;
name = "A" + i + "_TP" + type;
a[i] = cp.IntervalVar(d, name);
IIntervalVar[] alt = new IIntervalVar[2];
name = "A" + i + "_M1_TP" + type;
a1[i] = cp.IntervalVar(name);
a1[i].SetOptional();
alt[0] = a1[i];
name = "A" + i + "_M2_TP" + type;
a2[i] = cp.IntervalVar(name);
a2[i].SetOptional();
alt[1] = a2[i];
cp.Add(cp.Alternative(a[i], alt));
}
IIntervalSequenceVar s1 = cp.IntervalSequenceVar(a1, tp);
IIntervalSequenceVar s2 = cp.IntervalSequenceVar(a2, tp);
cp.Add(cp.NoOverlap(s1, setup1, true));
cp.Add(cp.NoOverlap(s2, setup2, true));
IIntExpr nbLongSetups = cp.IntExpr();
for (i = 0; i < NbTasks; ++i)
{
int tpi = TaskType[i];
int[] isLongSetup1 = new int[NbTypes + 1];
int[] isLongSetup2 = new int[NbTypes + 1];
for (j = 0; j < NbTypes; ++j)
{
isLongSetup1[j] = (30 <= SetupM1[NbTypes * tpi + j]) ? 1 : 0;
isLongSetup2[j] = (30 <= SetupM2[NbTypes * tpi + j]) ? 1 : 0;
}
isLongSetup1[NbTypes] = 0; // Last on resource or resource not selected
isLongSetup2[NbTypes] = 0; // Last on resource or resource not selected
nbLongSetups = cp.Sum(nbLongSetups,
cp.Element(isLongSetup1, cp.TypeOfNext(s1, a1[i], NbTypes, NbTypes)));
nbLongSetups = cp.Sum(nbLongSetups,
cp.Element(isLongSetup2, cp.TypeOfNext(s2, a2[i], NbTypes, NbTypes)));
}
cp.Add(cp.Minimize(nbLongSetups));
cp.SetParameter(CP.IntParam.FailLimit, 100000);
cp.SetParameter(CP.IntParam.LogPeriod, 10000);
if (cp.Solve())
{
Console.WriteLine("Machine 1: ");
IIntervalVar x;
for (x = cp.GetFirst(s1); !x.Equals(cp.GetLast(s1)); x = cp.GetNext(s1, x))
{
Console.WriteLine(cp.GetDomain(x));
}
Console.WriteLine(cp.GetDomain(x));
Console.WriteLine("Machine 2: ");
for (x = cp.GetFirst(s2); !x.Equals(cp.GetLast(s2)); x = cp.GetNext(s2, x))
{
Console.WriteLine(cp.GetDomain(x));
}
Console.WriteLine(cp.GetDomain(x));
Console.WriteLine("Number of long transition times \t: " + cp.ObjValue);
}
else
{
Console.WriteLine("No solution found.");
}
}
catch (IloException e)
{
Console.WriteLine("Error: " + e);
}
}
public static void Main(String[] args)
{
try
{
CP cp = new CP();
ITransitionDistance setup1 = cp.TransitionDistance(NbTypes);
ITransitionDistance setup2 = cp.TransitionDistance(NbTypes);
int i, j;
for (i = 0; i < NbTypes; ++i)
{
for (j = 0; j < NbTypes; ++j)
{
int d1 = SetupM1[NbTypes * i + j];
if (d1 < 0)
{
d1 = CP.IntervalMax; // Forbidden transition
}
setup1.SetValue(i, j, d1);
int d2 = SetupM2[NbTypes * i + j];
if (d2 < 0)
{
d2 = CP.IntervalMax; // Forbidden transition
}
setup2.SetValue(i, j, d2);
}
}
int[] tp = new int[NbTasks];
IIntervalVar[] a = new IIntervalVar[NbTasks];
IIntervalVar[] a1 = new IIntervalVar[NbTasks];
IIntervalVar[] a2 = new IIntervalVar[NbTasks];
IIntExpr[] ends = new IIntExpr[NbTasks];
String name;
for (i = 0; i < NbTasks; ++i)
{
int type = TaskType[i];
int d1 = TaskDurM1[i];
int d2 = TaskDurM2[i];
tp[i] = type;
name = "A" + i + "_TP" + type;
a[i] = cp.IntervalVar(name);
IIntervalVar[] alt = new IIntervalVar[2];
name = "A" + i + "_M1_TP" + type;
a1[i] = cp.IntervalVar(d1, name);
a1[i].SetOptional();
alt[0] = a1[i];
name = "A" + i + "_M2_TP" + type;
a2[i] = cp.IntervalVar(d2, name);
a2[i].SetOptional();
alt[1] = a2[i];
cp.Add(cp.Alternative(a[i], alt));
ends[i] = cp.EndOf(a[i]);
}
IIntervalSequenceVar s1 = cp.IntervalSequenceVar(a1, tp);
IIntervalSequenceVar s2 = cp.IntervalSequenceVar(a2, tp);
cp.Add(cp.NoOverlap(s1, setup1, true));
cp.Add(cp.NoOverlap(s2, setup2, true));
cp.Add(cp.Minimize(cp.Max(ends)));
cp.SetParameter(CP.IntParam.FailLimit, 100000);
cp.SetParameter(CP.IntParam.LogPeriod, 10000);
if (cp.Solve())
{
Console.WriteLine("Machine 1: ");
IIntervalVar x;
for (x = cp.GetFirst(s1); !x.Equals(cp.GetLast(s1)); x = cp.GetNext(s1, x))
{
Console.WriteLine(cp.GetDomain(x));
}
Console.WriteLine(cp.GetDomain(x));
Console.WriteLine("Machine 2: ");
for (x = cp.GetFirst(s2); !x.Equals(cp.GetLast(s2)); x = cp.GetNext(s2, x))
{
Console.WriteLine(cp.GetDomain(x));
}
Console.WriteLine(cp.GetDomain(x));
Console.WriteLine("Makespan \t: " + cp.ObjValue);
}
else
{
Console.WriteLine("No solution found.");
}
}
catch (IloException e)
{
Console.WriteLine("Error: " + e);
}
}
static void Main(string[] args)
{
int D = 5;
int W = 5;
int H = 3;
int G = 2;
int T = 12;
int[] k_g = new int[] { 2, 2 };
int ALLK = 4;
int[] cc_d = new int[] { 2, 1, 2, 1, 2 };
int[] ave = new int[] { 1, 0, 0, 1, 0, 0, 1, 1, 1, 1, 1, 1 };
int[] dur = new int[] { 1, 2, 1, 1, 2 };
int[] prf_D = new int[] { 2, 1, 1, 1, 100 };
int[] indexg_d = new int[] { 0, 1, 1, 1, 0 };
CP roster = new CP();
// intern availbility
INumToNumStepFunction resource_AveIntern = roster.NumToNumStepFunction(0, T, 100, "AvailibilityOfIntern");
for (int t = 0; t < T; t++)
{
if (ave[t] == 0)
{
resource_AveIntern.SetValue(t, t + 1, 0);
}
}
// discipline
IIntervalVar[] discipline_d = new IIntervalVar[D];
ICumulFunctionExpr hospitalNotRR = roster.CumulFunctionExpr();
for (int d = 0; d < D; d++)
{
discipline_d[d] = roster.IntervalVar();
discipline_d[d].EndMax = T;
discipline_d[d].EndMin = dur[d];
discipline_d[d].LengthMax = dur[d];
discipline_d[d].LengthMin = dur[d];
discipline_d[d].SizeMax = dur[d];
discipline_d[d].SizeMin = dur[d];
discipline_d[d].StartMax = T;
discipline_d[d].StartMin = 0;
discipline_d[d].SetIntensity(resource_AveIntern, 100);
hospitalNotRR.Add(roster.Pulse(discipline_d[d], 1));
discipline_d[d].SetOptional();
}
IIntervalSequenceVar dis = roster.IntervalSequenceVar(discipline_d);
roster.Add(roster.Ge(roster.PresenceOf(discipline_d[1]), roster.PresenceOf(discipline_d[4])));
roster.Add(roster.Before(dis, discipline_d[1], discipline_d[4]));
roster.Add(roster.NoOverlap(discipline_d));
// desciplien for not renewable resources
IIntVar[] height_t = new IIntVar[T];
for (int t = 0; t < T; t++)
{
height_t[t] = roster.IntVar(0, 1);
}
INumToNumSegmentFunction piecewise = roster.NumToNumSegmentFunction(new double[] { 0, 0, 1, 1, 2, 2, 3, 3, 4, 4, 5, 5, 6, 6, 7, 7, 8, 8, 9, 9, 10, 10, 11, 11 },
new double[] { 10, 0, 10, 1, 10, 2, 10, 3, 10, 4, 10, 5, 10, 6, 10, 7, 10, 8, 10, 9, 10, 10, 10, 11 });
INumExpr rc = roster.NumExpr();
for (int d = 0; d < D; d++)
{
rc = roster.Sum(rc, roster.StartEval(discipline_d[d], piecewise, 0));
}
for (int t = 0; t < T; t++)
{
}
IIntervalVar[] disciplineNR_d = new IIntervalVar[D];
for (int d = 0; d < D; d++)
{
disciplineNR_d[d] = roster.IntervalVar();
disciplineNR_d[d].EndMax = T;
disciplineNR_d[d].EndMin = T;
disciplineNR_d[d].LengthMax = T;
disciplineNR_d[d].LengthMin = T;
disciplineNR_d[d].SizeMax = T;
disciplineNR_d[d].SizeMin = T;
disciplineNR_d[d].StartMax = T;
disciplineNR_d[d].StartMin = 0;
disciplineNR_d[d].SetOptional();
roster.IfThen(roster.PresenceOf(discipline_d[d]), roster.PresenceOf(disciplineNR_d[d]));
}
//roster.Add(roster.IfThen(roster.PresenceOf(discipline_d[4]), roster.And(roster.Le(roster.EndOf(discipline_d[4]), roster.StartOf(discipline_d[0])),roster.PresenceOf(discipline_d[0]))));
//roster.Add(roster.StartBeforeEnd(discipline_d[4],discipline_d[0]));
// hospital changes
//ICumulFunctionExpr[] hospital
//for (int d = 0; d < D; d++)
//{
// roster.IfThen(roster.PresenceOf(disciplineNR_d[d]),);
//}
// hospital assignment
IIntervalVar[][] Hospital_dh = new IIntervalVar[D][];
for (int d = 0; d < D; d++)
{
Hospital_dh[d] = new IIntervalVar[H];
for (int h = 0; h < H; h++)
{
Hospital_dh[d][h] = roster.IntervalVar();
Hospital_dh[d][h].EndMax = T;
Hospital_dh[d][h].EndMin = dur[d];
Hospital_dh[d][h].LengthMax = dur[d];
Hospital_dh[d][h].LengthMin = dur[d];
Hospital_dh[d][h].SizeMax = dur[d];
Hospital_dh[d][h].SizeMin = dur[d];
Hospital_dh[d][h].StartMax = T;
Hospital_dh[d][h].StartMin = 0;
Hospital_dh[d][h].SetOptional();
if (h == 0 && (d != 4))
{
Hospital_dh[d][h].SetAbsent();
}
if (h == 1 && (d == 4))
{
Hospital_dh[d][h].SetAbsent();
}
if (h == 2 && (d == 4))
{
Hospital_dh[d][h].SetAbsent();
}
}
roster.Add(roster.Alternative(discipline_d[d], Hospital_dh[d]));
}
IIntervalVar[] disHospSetUp_dh = new IIntervalVar[D * H];
int[] type = new int[D * H];
for (int dh = 0; dh < D * H; dh++)
{
int dIndex = dh % D;
int hIndex = dh / D;
disHospSetUp_dh[dh] = roster.IntervalVar("DsiHosp" + "[" + dIndex + "][" + hIndex + "]");
type[dh] = hIndex;
disHospSetUp_dh[dh].SetOptional();
disHospSetUp_dh[dh] = Hospital_dh[dIndex][hIndex];
}
// changes
IIntervalSequenceVar cc = roster.IntervalSequenceVar(disHospSetUp_dh, type);
roster.NoOverlap(cc);
IIntVar[][] change_dD = new IIntVar[D][];
for (int d = 0; d < D; d++)
{
change_dD[d] = new IIntVar[D];
for (int dd = 0; dd < D; dd++)
{
change_dD[d][dd] = roster.IntVar(0, 1, "change_dD[" + d + "][" + dd + "]");
}
}
IIntVar[] change_d = new IIntVar[D];
for (int d = 0; d < D; d++)
{
change_d[d] = roster.IntVar(0, 1, "change_d[" + d + "]");
}
for (int dh = 0; dh < D * H; dh++)
{
int dIndex = dh % D;
int hIndex = dh / D;
IIntExpr chngD = roster.IntExpr();
chngD = roster.Sum(chngD, change_d[dIndex]);
roster.Add(roster.IfThen(roster.And(roster.PresenceOf(disHospSetUp_dh[dh]), roster.Neq(roster.TypeOfNext(cc, disHospSetUp_dh[dh], hIndex, hIndex), hIndex)), roster.Eq(chngD, 1)));
for (int ddh = 0; ddh < D * H; ddh++)
{
int ddIndex = ddh % D;
int hhIndex = ddh / D;
if (hhIndex == hIndex || dIndex == ddIndex)
{
continue;
}
}
}
//IIntVar[][] y_dD = new IIntVar[D][];
//for (int d = 0; d < D; d++)
//{
// y_dD[d] = new IIntVar[D];
// for (int dd= 0; dd < D; dd++)
// {
// y_dD[d][dd] = roster.IntVar(0,1);
// if (d == dd)
// {
// y_dD[d][dd] = roster.IntVar(0, 0);
// }
// }
//}
//for (int d = 0; d < D; d++)
//{
// for (int dd = 0; dd < D; dd++)
// {
// if (d != dd)
// {
// for (int h = 0; h < H; h++)
// {
// for (int hh = 0; hh < H; hh++)
// {
// if (d != dd && h != hh && true)
// {
// IIntExpr yyy = roster.IntExpr();
// yyy = roster.Sum(yyy,roster.Prod(T,y_dD[d][dd]));
// yyy = roster.Sum(yyy, roster.Prod(1, roster.EndOf(Hospital_dh[dd][hh])));
// yyy = roster.Sum(yyy, roster.Prod(-1, roster.StartOf(Hospital_dh[d][h])));
// roster.Add( roster.IfThen(roster.And(roster.PresenceOf(Hospital_dh[d][h]), roster.PresenceOf(Hospital_dh[dd][hh])), roster.AddGe(yyy, 0)));
// }
// }
// }
// }
// }
//}
//for (int d = 0; d < D; d++)
//{
// for (int dd = 0; dd < D; dd++)
// {
// if (d == dd)
// {
// continue;
// }
// IIntExpr change = roster.IntExpr();
// change = roster.Sum(change, change_dD[dd][d]);
// change = roster.Sum(change, roster.Prod(-1, y_dD[dd][d]));
// for (int ddd = 0; ddd < D; ddd++)
// {
// if (ddd == d || ddd == dd)
// {
// continue;
// }
// change = roster.Sum(change, change_dD[dd][ddd]);
// }
// roster.Add(roster.IfThen(roster.And(roster.PresenceOf(discipline_d[d]), roster.PresenceOf(discipline_d[dd])), roster.AddEq(change, 0)));
// }
//}
// all group assignment
IIntExpr allPossibleCourses = roster.IntExpr();
for (int d = 0; d < D; d++)
{
allPossibleCourses = roster.Sum(allPossibleCourses, roster.Prod(cc_d[d], roster.PresenceOf(discipline_d[d])));
}
roster.AddEq(allPossibleCourses, ALLK);
// group assignment
for (int g = 0; g < G; g++)
{
IIntExpr groupedCours_g = roster.IntExpr();
for (int d = 0; d < D; d++)
{
if (indexg_d[d] == g)
{
groupedCours_g = roster.Sum(groupedCours_g, roster.Prod(cc_d[d], roster.PresenceOf(discipline_d[d])));
}
}
roster.AddGe(groupedCours_g, k_g[g]);
}
// stay in one hospital
// objective function
INumExpr objExp = roster.NumExpr();
// discipline desire
for (int d = 0; d < D; d++)
{
objExp = roster.Sum(objExp, roster.Prod(prf_D[d], roster.PresenceOf(discipline_d[d])));
for (int dd = 0; dd < D; dd++)
{
objExp = roster.Sum(objExp, roster.Prod(-1, change_d[d]));
}
}
objExp = roster.Sum(objExp, rc);
IIntExpr makespan = roster.IntExpr();
for (int d = 0; d < D; d++)
{
makespan = roster.Max(makespan, roster.EndOf(discipline_d[d]));
}
IIntVar wait = roster.IntVar(0, T);
IIntExpr waitConst = roster.IntExpr();
waitConst = roster.Sum(waitConst, wait);
waitConst = roster.Sum(waitConst, roster.Prod(-1, makespan));
for (int d = 0; d < D; d++)
{
waitConst = roster.Sum(waitConst, roster.Prod(dur[d], roster.PresenceOf(discipline_d[d])));
}
roster.AddEq(waitConst, 0);
roster.AddMaximize(objExp);
roster.ExportModel("Roster.cpo");
roster.SetParameter(CP.IntParam.TimeMode, CP.ParameterValues.ElapsedTime);
roster.SetParameter(CP.IntParam.LogVerbosity, CP.ParameterValues.Quiet);
roster.SetParameter(CP.IntParam.SolutionLimit, 10);
// solve it now
if (roster.Solve())
{
Console.WriteLine("this is the cost of the CP column {0}", roster.ObjValue);
for (int d = 0; d < D; d++)
{
if (roster.IsPresent(discipline_d[d]))
{
Console.WriteLine("Discipline {0} with CC {1} and Dur {2} and Prf {3} started at time {4} and finished at time {5}", d, cc_d[d], dur[d], prf_D[d], roster.GetStart(discipline_d[d]), roster.GetEnd(discipline_d[d]));
}
}
for (int d = 0; d < D; d++)
{
for (int h = 0; h < H; h++)
{
if (roster.IsPresent(Hospital_dh[d][h]))
{
Console.WriteLine("Discipline {0} with CC {1} and Dur {2} and Prf {3} started at time {4} and finished at time {5} at Hospitail {6}", d, cc_d[d], dur[d], prf_D[d], roster.GetStart(Hospital_dh[d][h]), roster.GetEnd(Hospital_dh[d][h]), h);
}
}
}
for (int d = 0; d < D * H; d++)
{
int dIndex = d % D;
int hIndex = d / D;
if (roster.IsPresent(disHospSetUp_dh[d]))
{
Console.WriteLine("discpline " + dIndex + " in hospital " + hIndex);
}
}
for (int d = 0; d < D; d++)
{
if (roster.GetValue(change_d[d]) > 0.5)
{
Console.WriteLine("We have change for discipline {0}", d);
}
for (int dd = 0; dd < D; dd++)
{
if (d == dd)
{
continue;
}
}
}
Console.WriteLine("=========================================");
Console.WriteLine("Wainting time {0}", roster.GetValue(wait));
}
}
public static IIntExpr Game(CP cp, IIntExpr h, IIntExpr a, int n)
{
return cp.Diff(cp.Sum(cp.Prod(h, n - 1), a), cp.Gt(a, h));
}
public static void Main(String[] args)
{
String filename = "../../../../examples/data/learningeffect_default.data";
int nbJobs, nbMachines;
if (args.Length > 0)
{
filename = args[0];
}
CP cp = new CP();
DataReader data = new DataReader(filename);
nbJobs = data.Next();
nbMachines = data.Next();
IIntExpr[] ends = new IIntExpr[nbJobs];
IIntervalVar[][] machines = new IIntervalVar[nbMachines][];
int[][] sizes = new int[nbMachines][];
for (int j = 0; j < nbMachines; j++)
{
machines[j] = new IIntervalVar[nbJobs];
sizes[j] = new int[nbJobs];
}
for (int i = 0; i < nbJobs; i++)
{
IIntervalVar prec = cp.IntervalVar();
for (int j = 0; j < nbMachines; j++)
{
int m, d;
m = data.Next();
d = data.Next();
IIntervalVar ti = cp.IntervalVar(0, d);
machines[m][i] = ti;
sizes[m][i] = d;
if (j > 0)
{
cp.Add(cp.EndBeforeStart(prec, ti));
}
prec = ti;
}
ends[i] = cp.EndOf(prec);
}
for (int j = 0; j < nbMachines; j++)
{
double alpha = data.Next() / ((double)100);
IIntervalVar[] chain = new IIntervalVar[nbJobs];
IIntervalVar prec = cp.IntervalVar();
IIntExpr[] indices = new IIntExpr[nbJobs];
for (int i = 0; i < nbJobs; i++)
{
IIntervalVar syncti = cp.IntervalVar();
if (i > 0)
{
cp.Add(cp.EndBeforeStart(prec, syncti));
}
prec = syncti;
chain[i] = syncti;
IIntExpr index = cp.IntVar(0, nbJobs - 1);
indices[i] = index;
// Learning effect captured by the decreasing function
// of the position (0 <= alpha <= 1).
// At first position, in the sequence index = 0; there is no
// learning effect and duration of the task is its nominal duration
INumExpr floatDur = cp.Prod(sizes[j][i], cp.Power(alpha, index));
cp.Add(cp.Le(
cp.Abs(cp.Diff(floatDur, cp.SizeOf(machines[j][i]))),
0.5)
);
}
cp.Add(cp.Isomorphism(chain, machines[j], indices, nbJobs));
// The no-overlap is a redundant constraint in this quite
// simple model - it is used only to provide stronger inference.
cp.Add(cp.NoOverlap(machines[j]));
}
IObjective objective = cp.Minimize(cp.Max(ends));
cp.Add(objective);
cp.SetParameter(CP.IntParam.LogPeriod, 10000);
Console.WriteLine("Instance \t: " + filename);
if (cp.Solve())
{
Console.WriteLine("Makespan \t: " + cp.ObjValue);
}
else
{
Console.WriteLine("No solution found.");
}
}
public static IIntExpr Game(CP cp, IIntExpr h, IIntExpr a, int n)
{
return(cp.Diff(cp.Sum(cp.Prod(h, n - 1), a), cp.Gt(a, h)));
}
static void Main(string[] args)
{
String filename;
if (args.Length > 0)
{
filename = args[0];
}
else
{
filename = "../../../../examples/data/plant_location.data";
}
DataReader data = new DataReader(filename);
int nbCustomer = data.Next();
int nbLocation = data.Next();
int[][] cost = new int[nbCustomer][];
for (int c = 0; c < nbCustomer; c++)
{
cost[c] = new int[nbLocation];
for (int l = 0; l < nbLocation; l++)
{
cost[c][l] = data.Next();
}
}
int[] demand = new int[nbCustomer];
int totalDemand = 0;
for (int c = 0; c < nbCustomer; c++)
{
demand[c] = data.Next();
totalDemand += demand[c];
}
int[] fixedCost = new int[nbLocation];
for (int l = 0; l < nbLocation; l++)
{
fixedCost[l] = data.Next();
}
int[] capacity = new int[nbLocation];
for (int l = 0; l < nbLocation; l++)
{
capacity[l] = data.Next();
}
CP cp = new CP();
IIntVar[] cust = new IIntVar[nbCustomer];
for (int c = 0; c < nbCustomer; c++)
{
cust[c] = cp.IntVar(0, nbLocation - 1);
}
IIntVar[] open = new IIntVar[nbLocation];
IIntVar[] load = new IIntVar[nbLocation];
for (int l = 0; l < nbLocation; l++)
{
open[l] = cp.IntVar(0, 1);
load[l] = cp.IntVar(0, capacity[l]);
}
for (int l = 0; l < nbLocation; l++)
{
cp.Add(cp.Eq(open[l], cp.Gt(load[l], 0)));
}
cp.Add(cp.Pack(load, cust, demand));
IIntExpr obj = cp.Prod(open, fixedCost);
for (int c = 0; c < nbCustomer; c++)
{
obj = cp.Sum(obj, cp.Element(cost[c], cust[c]));
}
cp.Add(cp.Minimize(obj));
cp.AddKPI(cp.Quot(totalDemand, cp.ScalProd(open, capacity)), "Mean occupancy");
INumExpr[] usage = new INumExpr[nbLocation];
for (int w = 0; w < nbLocation; w++)
{
usage[w] = cp.Sum(cp.Quot(load[w], capacity[w]), cp.Diff(1, open[w]));
}
cp.AddKPI(cp.Min(usage), "Min occupancy");
int[] custValues =
{
19, 0, 11, 8, 29, 9, 29, 28, 17, 15, 7, 9, 18, 15, 1, 17, 25, 18, 17, 27,
22, 1, 26, 3, 22, 2, 20, 27, 2, 16, 1, 16, 12, 28, 19, 2, 20, 14, 13, 27,
3, 9, 18, 0, 13, 19, 27, 14, 12, 1, 15, 14, 17, 0, 7, 12, 11, 0, 25, 16,
22, 13, 16, 8, 18, 27, 19, 23, 26, 13, 11, 11, 19, 22, 28, 26, 23, 3, 18, 23,
26, 14, 29, 18, 9, 7, 12, 27, 8, 20
};
ISolution sol = cp.Solution();
for (int c = 0; c < nbCustomer; c++)
{
sol.SetValue(cust[c], custValues[c]);
}
cp.SetStartingPoint(sol);
cp.SetParameter(CP.DoubleParam.TimeLimit, 10);
cp.SetParameter(CP.IntParam.LogPeriod, 10000);
cp.Solve();
}
public static void Main(String[] args)
{
CP cp = new CP();
dist[0] = new int[] { 16, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 1, 1, 0, 0, 0, 2, 2, 1, 1, 1 };
dist[1] = new int[] { 1, 16, 2, 0, 0, 0, 0, 0, 2, 2, 1, 1, 1, 2, 2, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0 };
dist[2] = new int[] { 1, 2, 16, 0, 0, 0, 0, 0, 2, 2, 1, 1, 1, 2, 2, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0 };
dist[3] = new int[] { 0, 0, 0, 16, 2, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1 };
dist[4] = new int[] { 0, 0, 0, 2, 16, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1 };
dist[5] = new int[] { 0, 0, 0, 2, 2, 16, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1 };
dist[6] = new int[] { 0, 0, 0, 0, 0, 0, 16, 2, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 2, 0, 0, 0, 1, 1 };
dist[7] = new int[] { 0, 0, 0, 0, 0, 0, 2, 16, 0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 2, 0, 0, 0, 1, 1 };
dist[8] = new int[] { 1, 2, 2, 0, 0, 0, 0, 0, 16, 2, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1 };
dist[9] = new int[] { 1, 2, 2, 0, 0, 0, 0, 0, 2, 16, 2, 2, 2, 2, 2, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1 };
dist[10] = new int[] { 1, 1, 1, 0, 0, 0, 1, 1, 2, 2, 16, 2, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 0, 1, 1 };
dist[11] = new int[] { 1, 1, 1, 0, 0, 0, 1, 1, 2, 2, 2, 16, 2, 2, 2, 2, 2, 1, 1, 2, 1, 1, 0, 1, 1 };
dist[12] = new int[] { 1, 1, 1, 0, 0, 0, 1, 1, 2, 2, 2, 2, 16, 2, 2, 2, 2, 1, 1, 2, 1, 1, 0, 1, 1 };
dist[13] = new int[] { 2, 2, 2, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 16, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
dist[14] = new int[] { 2, 2, 2, 0, 0, 0, 0, 0, 2, 2, 2, 2, 2, 2, 16, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 };
dist[15] = new int[] { 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 1, 1, 16, 2, 2, 2, 1, 2, 2, 1, 2, 2 };
dist[16] = new int[] { 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 2, 2, 2, 1, 1, 2, 16, 2, 2, 1, 2, 2, 1, 2, 2 };
dist[17] = new int[] { 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 16, 2, 2, 1, 1, 0, 2, 2 };
dist[18] = new int[] { 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 16, 2, 1, 1, 0, 2, 2 };
dist[19] = new int[] { 0, 0, 0, 1, 1, 1, 2, 2, 1, 1, 2, 2, 2, 1, 1, 1, 1, 2, 2, 16, 1, 1, 0, 1, 1 };
dist[20] = new int[] { 2, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 16, 2, 1, 2, 2 };
dist[21] = new int[] { 2, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 2, 16, 1, 2, 2 };
dist[22] = new int[] { 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 16, 1, 1 };
dist[23] = new int[] { 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 2, 1, 16, 2 };
dist[24] = new int[] { 1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 1, 2, 2, 1, 2, 16 };
int nbTransmitters = getTransmitterIndex(nbCell, 0);
IIntVar[] freq = cp.IntVarArray(nbTransmitters,
0, nbAvailFreq - 1, "freq");
for (int cell = 0; cell < nbCell; cell++)
{
for (int channel1 = 0; channel1 < nbChannel[cell]; channel1++)
{
for (int channel2 = channel1 + 1; channel2 < nbChannel[cell]; channel2++)
{
cp.Add(cp.Ge(cp.Abs(cp.Diff(freq[getTransmitterIndex(cell, channel1)],
freq[getTransmitterIndex(cell, channel2)])),
16));
}
}
}
for (int cell1 = 0; cell1 < nbCell; cell1++)
{
for (int cell2 = cell1 + 1; cell2 < nbCell; cell2++)
{
if (dist[cell1][cell2] > 0)
{
for (int channel1 = 0; channel1 < nbChannel[cell1]; channel1++)
{
for (int channel2 = 0; channel2 < nbChannel[cell2]; channel2++)
{
cp.Add(cp.Ge(cp.Abs(cp.Diff(freq[getTransmitterIndex(cell1, channel1)],
freq[getTransmitterIndex(cell2, channel2)])),
dist[cell1][cell2]));
}
}
}
}
}
// Minimizing the total number of frequencies
IIntExpr nbFreq = cp.CountDifferent(freq);
cp.Add(cp.Minimize(nbFreq));
cp.SetParameter(CP.IntParam.CountDifferentInferenceLevel,
CP.ParameterValues.Extended);
cp.SetParameter(CP.IntParam.FailLimit, 40000);
cp.SetParameter(CP.IntParam.LogPeriod, 100000);
if (cp.Solve())
{
for (int cell = 0; cell < nbCell; cell++)
{
for (int channel = 0; channel < nbChannel[cell]; channel++)
{
Console.Write(cp.GetIntValue(freq[getTransmitterIndex(cell, channel)])
+ " ");
}
Console.WriteLine();
}
Console.WriteLine("Total # of sites " + nbTransmitters);
Console.WriteLine("Total # of frequencies " + cp.GetValue(nbFreq));
}
else
{
Console.WriteLine("No solution");
}
cp.End();
}
static public void Main(string[] args)
{
int numPeriods = 6;
if (args.Length > 0)
{
numPeriods = Int32.Parse(args[0]);
}
CP cp = new CP();
//
// Variables
//
// Host boat choice
IIntVar[] host = new IIntVar[numBoats];
for (int j = 0; j < numBoats; j++)
{
host[j] = cp.IntVar(0, 1, String.Format("H{0}", j));
}
// Who is where each time period (time- and boat-based views)
IIntVar[][] timePeriod = new IIntVar[numPeriods][];
for (int i = 0; i < numPeriods; i++)
{
timePeriod[i] = new IIntVar[numBoats];
for (int j = 0; j < numBoats; j++)
{
timePeriod[i][j] = cp.IntVar(0, numBoats - 1, String.Format("T{0},{1}", i, j));
}
}
IIntVar[][] visits = Transpose(timePeriod);
//
// Objective
//
IIntVar numHosts = cp.IntVar(numPeriods, numBoats);
cp.Add(cp.Eq(numHosts, cp.Sum(host)));
cp.Add(cp.Minimize(numHosts));
//
// Constraints
//
// Stay in my boat (host) or only visit other boats (guest)
for (int i = 0; i < numBoats; i++)
{
cp.Add(cp.Eq(cp.Count(visits[i], i), cp.Prod(host[i], numPeriods)));
}
// Capacity constraints: only hosts have capacity
for (int p = 0; p < numPeriods; p++)
{
IIntVar[] load = new IIntVar[numBoats];
for (int j = 0; j < numBoats; j++)
{
load[j] = cp.IntVar(0, boatSize[j], String.Format("L{0},{1}", p, j));
cp.Add(cp.Le(load[j], cp.Prod(host[j], boatSize[j])));
}
cp.Add(cp.Pack(load, timePeriod[p], crewSize, numHosts));
}
// No two crews meet more than once
for (int i = 0; i < numBoats; i++)
{
for (int j = i + 1; j < numBoats; j++)
{
IIntExpr timesMet = cp.Constant(0);
for (int p = 0; p < numPeriods; p++)
{
timesMet = cp.Sum(timesMet, cp.Eq(visits[i][p], visits[j][p]));
}
cp.Add(cp.Le(timesMet, 1));
}
}
// Host and guest boat constraints: given in problem spec
cp.Add(cp.Eq(host[0], 1));
cp.Add(cp.Eq(host[1], 1));
cp.Add(cp.Eq(host[2], 1));
cp.Add(cp.Eq(host[39], 0));
cp.Add(cp.Eq(host[40], 0));
cp.Add(cp.Eq(host[41], 0));
//
// Solving
//
if (cp.Solve())
{
Console.WriteLine("Solution at cost = {0}", cp.GetValue(numHosts));
Console.Write("Hosts: ");
for (int i = 0; i < numBoats; i++)
{
Console.Write(cp.GetValue(host[i]));
}
Console.WriteLine();
for (int p = 0; p < numPeriods; p++)
{
Console.WriteLine("Period {0}", p);
for (int h = 0; h < numBoats; h++)
{
if (cp.GetValue(host[h]) > 0)
{
Console.Write("\tHost {0} : ", h);
int load = 0;
for (int i = 0; i < numBoats; i++)
{
if (cp.GetValue(visits[i][p]) == h)
{
load += crewSize[i];
Console.Write("{0} ({1}) ", i, crewSize[i]);
}
}
Console.WriteLine(" --- {0} / {1}", load, boatSize[h]);
}
}
}
Console.WriteLine();
}
}
/*
* MakeTeamTuples return a IIntTupleSet containing all the possible configurations of a team.
* The team members in a tuple are ordered to break symmetry.
*/
public static IIntTupleSet MakeTeamTuples(CP mainCP)
{
CP cp = new CP();
int i;
int[] newEmployee = new int[nbPersons];
int[] service = new int[nbPersons];
for (i = 0; i < nbPersons; i++)
{
if ((i % 2) == 0)
{
newEmployee[i] = 1;
}
else
{
newEmployee[i] = 0;
}
if (i < 20)
{
service[i] = 0;
}
else if (i < 40)
{
service[i] = 1;
}
else if (i < 45)
{
service[i] = 2;
}
else if (i < 50)
{
service[i] = 3;
}
else if (i < 55)
{
service[i] = 4;
}
else
{
service[i] = 5;
}
}
IIntTupleSet ts = mainCP.IntTable(teamSize);
IIntVar[] teamMembers = cp.IntVarArray(teamSize, 0, nbPersons - 1);
//number of new employees among the teamMembers = number of teamMembers / 2
IIntExpr nbNewEmployees = cp.Constant(0);
for (i = 0; i < teamSize; i++)
{
nbNewEmployees = cp.Sum(nbNewEmployees, cp.Element(newEmployee, teamMembers[i]));
}
cp.Add(cp.Eq(nbNewEmployees, teamSize / 2));
//a new employee and his coach must be in the same team
for (i = 0; i < 60; i += 2)
{
if (coaching[i] >= 0)
{
cp.Add(cp.Eq(cp.Count(teamMembers, i), cp.Count(teamMembers, coaching[i])));
}
}
IIntVar[] serviceVar = cp.IntVarArray(teamSize, 0, numServices - 1);
for (i = 0; i < teamSize; i++)
{
cp.Add(cp.Eq(serviceVar[i], cp.Element(service, teamMembers[i])));
}
// at most 4 people of the same service
for (i = 0; i < numServices; i++)
{
cp.Add(cp.Le(cp.Count(serviceVar, i), 4));
}
//Persons of Services A and B cannot be in the same team
//Persons of Services E and F cannot be in the same team
cp.Add(cp.Or(cp.Eq(cp.Count(serviceVar, 0), 0), cp.Eq(cp.Count(serviceVar, 1), 0)));
cp.Add(cp.Or(cp.Eq(cp.Count(serviceVar, 4), 0), cp.Eq(cp.Count(serviceVar, 5), 0)));
// order the teamMembers to break symmetry
for (i = 0; i < teamSize - 1; i++)
{
cp.Add(cp.Lt(teamMembers[i], teamMembers[i + 1]));
}
int[] tuple = new int[teamSize];
cp.SetParameter(CP.IntParam.LogVerbosity,
CP.ParameterValues.Quiet);
cp.SetParameter(CP.IntParam.SearchType,
CP.ParameterValues.DepthFirst);
cp.StartNewSearch();
while (cp.Next())
{
for (i = 0; i < teamSize; i++)
{
tuple[i] = (int)cp.GetValue(teamMembers[i]);
}
cp.AddTuple(ts, tuple);
}
return(ts);
}
public static void Main(String[] args)
{
String filename = "../../../../examples/data/rcpspmm_default.data";
int failLimit = 30000;
int nbTasks, nbRenewable, nbNonRenewable;
if (args.Length > 0)
filename = args[0];
if (args.Length > 1)
failLimit = Convert.ToInt32(args[1]);
CP cp = new CP();
DataReader data = new DataReader(filename);
nbTasks = data.Next();
nbRenewable = data.Next();
nbNonRenewable = data.Next();
ICumulFunctionExpr[] renewables = new ICumulFunctionExpr[nbRenewable];
IIntExpr[] nonRenewables = new IIntExpr[nbNonRenewable];
int[] capRenewables = new int[nbRenewable];
int[] capNonRenewables = new int[nbNonRenewable];
for (int j = 0; j < nbRenewable; j++)
{
renewables[j] = cp.CumulFunctionExpr();
capRenewables[j] = data.Next();
}
for (int j = 0; j < nbNonRenewable; j++)
{
nonRenewables[j] = cp.IntExpr();
capNonRenewables[j] = data.Next();
}
IIntervalVar[] tasks = new IIntervalVar[nbTasks];
List<IIntervalVar>[] modes = new List<IIntervalVar>[nbTasks];
for (int i = 0; i < nbTasks; i++)
{
tasks[i] = cp.IntervalVar();
modes[i] = new List<IIntervalVar>();
}
List<IIntExpr> ends = new List<IIntExpr>();
for (int i = 0; i < nbTasks; i++)
{
IIntervalVar task = tasks[i];
int d = data.Next();
int nbModes = data.Next();
int nbSucc = data.Next();
for (int k = 0; k < nbModes; k++)
{
IIntervalVar alt = cp.IntervalVar();
alt.SetOptional();
modes[i].Add(alt);
}
cp.Add(cp.Alternative(task, modes[i].ToArray()));
ends.Add(cp.EndOf(task));
for (int s = 0; s < nbSucc; s++)
{
int succ = data.Next();
cp.Add(cp.EndBeforeStart(task, tasks[succ]));
}
}
for (int i = 0; i < nbTasks; i++)
{
IIntervalVar task = tasks[i];
List<IIntervalVar> imodes = modes[i];
for (int k = 0; k < imodes.Count; k++)
{
int taskId = data.Next();
int modeId = data.Next();
int d = data.Next();
imodes[k].SizeMin = d;
imodes[k].SizeMax = d;
int q;
for (int j = 0; j < nbNonRenewable; j++)
{
q = data.Next();
if (0 < q)
{
renewables[j].Add(cp.Pulse(imodes[k], q));
}
}
for (int j = 0; j < nbNonRenewable; j++)
{
q = data.Next();
if (0 < q)
{
nonRenewables[j] = cp.Sum(nonRenewables[j], cp.Prod(q, cp.PresenceOf(imodes[k])));
}
}
}
}
for (int j = 0; j < nbRenewable; j++)
{
cp.Add(cp.Le(renewables[j], capRenewables[j]));
}
for (int j = 0; j < nbRenewable; j++)
{
cp.Add(cp.Le(nonRenewables[j], capNonRenewables[j]));
}
IObjective objective = cp.Minimize(cp.Max(ends.ToArray()));
cp.Add(objective);
cp.SetParameter(CP.IntParam.FailLimit, failLimit);
Console.WriteLine("Instance \t: " + filename);
if (cp.Solve())
{
Console.WriteLine("Makespan \t: " + cp.ObjValue);
}
else
{
Console.WriteLine("No solution found.");
}
}
private void BuildModel()
{
// Create the decision variables, cost, and the model
scene = new IIntVar[numScenes];
for (int s = 0; s < numScenes; s++)
scene[s] = cp.IntVar(0, numScenes - 1);
// Expression representing the global cost
idleCost = cp.IntExpr();
// Make the slot-based secondary model
IIntVar[] slot = new IIntVar[numScenes];
for (int s = 0; s < numScenes; s++)
slot[s] = cp.IntVar(0, numScenes - 1);
cp.Add(cp.Inverse(scene, slot));
// Loop over all actors, building cost
for (int a = 0; a < numActors; a++)
{
// Expression for the waiting time for this actor
IIntExpr actorWait = cp.IntExpr();
// Calculate the first and last slots where this actor plays
List<IIntVar> position = new List<IIntVar>();
System.Collections.IEnumerator en = actorInScene[a].GetEnumerator();
while (en.MoveNext())
position.Add(slot[(int)en.Current]);
IIntExpr firstSlot = cp.Min(position.ToArray());
IIntExpr lastSlot = cp.Max(position.ToArray());
// If an actor is not in a scene, he waits
// if he is on set when the scene is filmed
for (int s = 0; s < numScenes; s++)
{
if (!actorInScene[a].Contains(s))
{ // not in scene
IIntExpr wait = cp.And(cp.Le(firstSlot, slot[s]), cp.Le(
slot[s], lastSlot));
actorWait = cp.Sum(actorWait, cp.Prod(sceneDuration[s],
wait));
}
}
// Accumulate the cost of waiting time for this actor
idleCost = cp.Sum(idleCost, cp.Prod(actorPay[a], actorWait));
}
cp.Add(cp.Minimize(idleCost));
}
static public void Main(string[] args)
{
CP cp = new CP();
int nbTruckConfigs = 7; // number of possible configurations for the truck
int nbOrders = 21;
int nbCustomers = 3;
int nbTrucks = 15; //max number of travels of the truck
int[] maxTruckConfigLoad = //Capacity of the truck depends on its config
{
11, 11, 11, 11, 10, 10, 10
};
int maxLoad = Max(maxTruckConfigLoad);
int[] customerOfOrder =
{
0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
1, 1, 1, 1, 1, 2, 2, 2, 2, 2,
2
};
int[] volumes =
{
3, 4, 3, 2, 5, 4, 11, 4, 5, 2,
4, 7, 3, 5, 2, 5, 6, 11, 1, 6,
3
};
int[] colors =
{
1, 2, 0, 1, 1, 1, 0, 0, 0, 0,
2, 2, 2, 0, 2, 1, 0, 2, 0, 0,
0
};
int[] truckCost = //cost for loading a truck of a given config
{
2, 2, 2, 3, 3, 3, 4
};
//Decision variables
IIntVar[] truckConfigs = cp.IntVarArray(nbTrucks, 0, nbTruckConfigs - 1); //configuration of the truck
IIntVar[] where = cp.IntVarArray(nbOrders, 0, nbTrucks - 1); //In which truck is an order
IIntVar[] load = cp.IntVarArray(nbTrucks, 0, maxLoad); //load of a truck
IIntVar numUsed = cp.IntVar(0, nbTrucks); // number of trucks used
IIntVar[] customerOfTruck = cp.IntVarArray(nbTrucks, 0, nbCustomers);
// transition costs between trucks
IIntTupleSet costTuples = cp.IntTable(3);
cp.AddTuple(costTuples, new int[] { 0, 0, 0 });
cp.AddTuple(costTuples, new int[] { 0, 1, 0 });
cp.AddTuple(costTuples, new int[] { 0, 2, 0 });
cp.AddTuple(costTuples, new int[] { 0, 3, 10 });
cp.AddTuple(costTuples, new int[] { 0, 4, 10 });
cp.AddTuple(costTuples, new int[] { 0, 5, 10 });
cp.AddTuple(costTuples, new int[] { 0, 6, 15 });
cp.AddTuple(costTuples, new int[] { 1, 0, 0 });
cp.AddTuple(costTuples, new int[] { 1, 1, 0 });
cp.AddTuple(costTuples, new int[] { 1, 2, 0 });
cp.AddTuple(costTuples, new int[] { 1, 3, 10 });
cp.AddTuple(costTuples, new int[] { 1, 4, 10 });
cp.AddTuple(costTuples, new int[] { 1, 5, 10 });
cp.AddTuple(costTuples, new int[] { 1, 6, 15 });
cp.AddTuple(costTuples, new int[] { 2, 0, 0 });
cp.AddTuple(costTuples, new int[] { 2, 1, 0 });
cp.AddTuple(costTuples, new int[] { 2, 2, 0 });
cp.AddTuple(costTuples, new int[] { 2, 3, 10 });
cp.AddTuple(costTuples, new int[] { 2, 4, 10 });
cp.AddTuple(costTuples, new int[] { 2, 5, 10 });
cp.AddTuple(costTuples, new int[] { 2, 6, 15 });
cp.AddTuple(costTuples, new int[] { 3, 0, 3 });
cp.AddTuple(costTuples, new int[] { 3, 1, 3 });
cp.AddTuple(costTuples, new int[] { 3, 2, 3 });
cp.AddTuple(costTuples, new int[] { 3, 3, 0 });
cp.AddTuple(costTuples, new int[] { 3, 4, 10 });
cp.AddTuple(costTuples, new int[] { 3, 5, 10 });
cp.AddTuple(costTuples, new int[] { 3, 6, 15 });
cp.AddTuple(costTuples, new int[] { 4, 0, 3 });
cp.AddTuple(costTuples, new int[] { 4, 1, 3 });
cp.AddTuple(costTuples, new int[] { 4, 2, 3 });
cp.AddTuple(costTuples, new int[] { 4, 3, 10 });
cp.AddTuple(costTuples, new int[] { 4, 4, 0 });
cp.AddTuple(costTuples, new int[] { 4, 5, 10 });
cp.AddTuple(costTuples, new int[] { 4, 6, 15 });
cp.AddTuple(costTuples, new int[] { 5, 0, 3 });
cp.AddTuple(costTuples, new int[] { 5, 1, 3 });
cp.AddTuple(costTuples, new int[] { 5, 2, 3 });
cp.AddTuple(costTuples, new int[] { 5, 3, 10 });
cp.AddTuple(costTuples, new int[] { 5, 4, 10 });
cp.AddTuple(costTuples, new int[] { 5, 5, 0 });
cp.AddTuple(costTuples, new int[] { 5, 6, 15 });
cp.AddTuple(costTuples, new int[] { 6, 0, 3 });
cp.AddTuple(costTuples, new int[] { 6, 1, 3 });
cp.AddTuple(costTuples, new int[] { 6, 2, 3 });
cp.AddTuple(costTuples, new int[] { 6, 3, 10 });
cp.AddTuple(costTuples, new int[] { 6, 4, 10 });
cp.AddTuple(costTuples, new int[] { 6, 5, 10 });
cp.AddTuple(costTuples, new int[] { 6, 6, 0 });
IIntVar[] transitionCost = cp.IntVarArray(nbTrucks - 1, 0, 1000);
for (int i = 1; i < nbTrucks; i++)
{
IIntVar[] auxVars = new IIntVar[3];
auxVars[0] = truckConfigs[i - 1];
auxVars[1] = truckConfigs[i];
auxVars[2] = transitionCost[i - 1];
cp.Add(cp.AllowedAssignments(auxVars, costTuples));
}
// constrain the volume of the orders in each truck
cp.Add(cp.Pack(load, where, volumes, numUsed));
for (int i = 0; i < nbTrucks; i++)
{
cp.Add(cp.Le(load[i], cp.Element(maxTruckConfigLoad, truckConfigs[i])));
}
// compatibility between the colors of an order and the configuration of its truck
int[][] allowedContainerConfigs = new int[3][];
allowedContainerConfigs[0] = new int[] { 0, 3, 4, 6 };
allowedContainerConfigs[1] = new int[] { 1, 3, 5, 6 };
allowedContainerConfigs[2] = new int[] { 2, 4, 5, 6 };
for (int j = 0; j < nbOrders; j++)
{
IIntVar configOfContainer = cp.IntVar(allowedContainerConfigs[colors[j]]);
cp.Add(cp.Eq(configOfContainer, cp.Element(truckConfigs, where[j])));
}
// only one customer per truck
for (int j = 0; j < nbOrders; j++)
{
cp.Add(cp.Eq(cp.Element(customerOfTruck, where[j]), customerOfOrder[j]));
}
// non used trucks are at the end
for (int j = 1; j < nbTrucks; j++)
{
cp.Add(cp.Or(cp.Gt(load[j - 1], 0), cp.Eq(load[j], 0)));
}
// Dominance: the non used trucks keep the last used configuration
cp.Add(cp.Gt(load[0], 0));
for (int i = 1; i < nbTrucks; i++)
{
cp.Add(cp.Or(cp.Gt(load[i], 0), cp.Eq(truckConfigs[i], truckConfigs[i - 1])));
}
//Dominance: regroup deliveries with same configuration
for (int i = nbTrucks - 2; i > 0; i--)
{
IConstraint Ct = cp.TrueConstraint();
for (int p = i + 1; p < nbTrucks; p++)
{
Ct = cp.And(cp.Neq(truckConfigs[p], truckConfigs[i - 1]), Ct);
}
cp.Add(cp.Or(cp.Eq(truckConfigs[i], truckConfigs[i - 1]), Ct));
}
// Objective: first criterion for minimizing the cost for configuring and loading trucks
// second criterion for minimizing the number of trucks
IIntExpr obj1 = cp.Constant(0);
for (int i = 0; i < nbTrucks; i++)
{
obj1 = cp.Sum(obj1, cp.Prod(cp.Element(truckCost, truckConfigs[i]), cp.Neq(load[i], 0)));
}
obj1 = cp.Sum(obj1, cp.Sum(transitionCost));
IIntExpr obj2 = numUsed;
// Multicriteria lexicographic optimization
cp.Add(cp.Minimize(cp.StaticLex(obj1, obj2)));
cp.SetParameter(CP.DoubleParam.TimeLimit, 20);
cp.SetParameter(CP.IntParam.LogPeriod, 50000);
cp.Solve();
double[] obj = cp.GetObjValues();
Console.WriteLine("Configuration cost: " + (int)obj[0] +
" Number of Trucks: " + (int)obj[1]);
for (int i = 0; i < nbTrucks; i++)
{
if (cp.GetValue(load[i]) > 0)
{
Console.Write("Truck " + i +
": Config=" + cp.GetIntValue(truckConfigs[i])
+ " Items= ");
for (int j = 0; j < nbOrders; j++)
{
if (cp.GetValue(where[j]) == i)
{
Console.Write("<" + j + "," + colors[j] + "," + volumes[j] + "> ");
}
}
Console.WriteLine();
}
}
}
public double SolveGoalProgramming(int branchLimit)
{
// Objective 1
Console.WriteLine();
Console.WriteLine(" ! ----------------------------------------------------------------------------");
Console.WriteLine(" ! STEP 1: Minimizing usage of expensive resources");
Console.WriteLine(" ! ----------------------------------------------------------------------------");
IIntExpr costExpr = cp.IntExpr();
for (int i = 0; i < nbJobs; i++)
{
for (int j = 0; j < nbMachines; j++)
{
if (costs[j][i] >= 1000)
{
costExpr = cp.Sum(costExpr, cp.Prod(costs[j][i], cp.PresenceOf(machines[j][i])));
}
}
}
IObjective obj1 = cp.Minimize(costExpr);
cp.Add(obj1);
cp.SetParameter(CP.IntParam.LogPeriod, 600000);
cp.SetParameter(CP.IntParam.BranchLimit, 2 * branchLimit / 3);
cp.SetParameter(CP.IntParam.NoOverlapInferenceLevel, CP.ParameterValues.Extended);
cp.Solve();
ISolution startSol = cp.Solution();
for (int i = 0; i < nbJobs; i++)
{
for (int j = 0; j < nbMachines; j++)
{
if (cp.IsPresent(machines[j][i]))
{
startSol.SetPresent(machines[j][i]);
startSol.SetStart(machines[j][i], cp.GetStart(machines[j][i]));
}
}
}
// Objective 2
Console.WriteLine();
Console.WriteLine(" ! ----------------------------------------------------------------------------");
Console.WriteLine(" ! STEP 2: Minimizing total cost");
Console.WriteLine(" ! ----------------------------------------------------------------------------");
cp.Remove(obj1);
IIntExpr costExpr2 = cp.IntExpr();
for (int i = 0; i < nbJobs; i++)
{
for (int j = 0; j < nbMachines; j++)
{
costExpr2 = cp.Sum(costExpr2, cp.Prod(costs[j][i], cp.PresenceOf(machines[j][i])));
}
}
IObjective obj2 = cp.Minimize(costExpr2);
cp.Add(obj2);
cp.SetParameter(CP.IntParam.BranchLimit, branchLimit / 3);
cp.SetStartingPoint(startSol);
cp.Solve();
double cost = cp.ObjValue;
return(cost);
}
static void Main(string[] args)
{
try
{
int n = 10;
if (args.Length > 0)
{
n = Int32.Parse(args[0]);
}
if ((n % 2) == 1)
{
n++;
}
Console.WriteLine("Finding schedule for {0} teams", n);
int nbWeeks = 2 * (n - 1);
int nbGamesPerWeek = n / 2;
int nbGames = n * (n - 1);
CP cp = new CP();
IIntVar[][] games = new IIntVar[nbWeeks][];
IIntVar[][] home = new IIntVar[nbWeeks][];
IIntVar[][] away = new IIntVar[nbWeeks][];
for (int i = 0; i < nbWeeks; i++)
{
home[i] = cp.IntVarArray(nbGamesPerWeek, 0, n - 1);
away[i] = cp.IntVarArray(nbGamesPerWeek, 0, n - 1);
games[i] = cp.IntVarArray(nbGamesPerWeek, 0, nbGames - 1);
}
//
// For each play slot, set up correspondance between game id,
// home team, and away team
//
IIntTupleSet gha = cp.IntTable(3);
int[] tuple = new int[3];
for (int i = 0; i < n; i++)
{
tuple[0] = i;
for (int j = 0; j < n; j++)
{
if (i != j)
{
tuple[1] = j;
tuple[2] = Game(i, j, n);
cp.AddTuple(gha, tuple);
}
}
}
for (int i = 0; i < nbWeeks; i++)
{
for (int j = 0; j < nbGamesPerWeek; j++)
{
IIntVar[] vars = cp.IntVarArray(3);
vars[0] = home[i][j];
vars[1] = away[i][j];
vars[2] = games[i][j];
cp.Add(cp.AllowedAssignments(vars, gha));
}
}
//
// All teams play each week
//
for (int i = 0; i < nbWeeks; i++)
{
IIntVar[] teamsThisWeek = cp.IntVarArray(n);
for (int j = 0; j < nbGamesPerWeek; j++)
{
teamsThisWeek[j] = home[i][j];
teamsThisWeek[nbGamesPerWeek + j] = away[i][j];
}
cp.Add(cp.AllDiff(teamsThisWeek));
}
//
// Dual representation: for each game id, the play slot is maintained
//
IIntVar[] weekOfGame = cp.IntVarArray(nbGames, 0, nbWeeks - 1);
IIntVar[] allGames = cp.IntVarArray(nbGames);
IIntVar[] allSlots = cp.IntVarArray(nbGames, 0, nbGames - 1);
for (int i = 0; i < nbWeeks; i++)
{
for (int j = 0; j < nbGamesPerWeek; j++)
{
allGames[i * nbGamesPerWeek + j] = games[i][j];
}
}
cp.Add(cp.Inverse(allGames, allSlots));
for (int i = 0; i < nbGames; i++)
{
cp.Add(cp.Eq(weekOfGame[i], cp.Div(allSlots[i], nbGamesPerWeek)));
}
//
// Two half schedules. Cannot play the same pair twice in the same half.
// Plus, impose a minimum number of weeks between two games involving
// the same teams (up to six weeks)
//
int mid = nbWeeks / 2;
int overlap = 0;
if (n >= 6)
{
overlap = min(n / 2, 6);
}
for (int i = 0; i < n; i++)
{
for (int j = i + 1; j < n; j++)
{
int g1 = Game(i, j, n);
int g2 = Game(j, i, n);
cp.Add(cp.Equiv(cp.Ge(weekOfGame[g1], mid), cp.Lt(weekOfGame[g2], mid)));
// Six week difference...
if (overlap != 0)
{
cp.Add(cp.Ge(cp.Abs(cp.Diff(weekOfGame[g1], weekOfGame[g2])), overlap));
}
}
}
//
// Can't have three homes or three aways in a row.
//
IIntVar[][] playHome = new IIntVar[n][];
for (int i = 0; i < n; i++)
{
playHome[i] = cp.IntVarArray(nbWeeks, 0, 1);
for (int j = 0; j < nbWeeks; j++)
{
cp.Add(cp.Eq(playHome[i][j], cp.Count(home[j], i)));
}
for (int j = 0; j < nbWeeks - 3; j++)
{
IIntVar[] window = cp.IntVarArray(3);
for (int k = j; k < j + 3; k++)
{
window[k - j] = playHome[i][k];
}
IIntExpr windowSum = cp.Sum(window);
cp.Add(cp.Le(1, windowSum));
cp.Add(cp.Le(windowSum, 2));
}
}
//
// If we start the season home, we finish away and vice versa.
//
for (int i = 0; i < n; i++)
{
cp.Add(cp.Neq(playHome[i][0], playHome[i][nbWeeks - 1]));
}
//
// Objective: minimize the number of `breaks'. A break is
// two consecutive home or away matches for a
// particular team
IIntVar[] teamBreaks = cp.IntVarArray(n, 0, nbWeeks / 2);
for (int i = 0; i < n; i++)
{
IIntExpr nbreaks = cp.Constant(0);
for (int j = 1; j < nbWeeks; j++)
{
nbreaks = cp.Sum(nbreaks, cp.IntExpr(cp.Eq(playHome[i][j - 1], playHome[i][j])));
}
cp.Add(cp.Eq(teamBreaks[i], nbreaks));
}
IIntVar breaks = cp.IntVar(n - 2, n * (nbWeeks / 2));
cp.Add(cp.Eq(breaks, cp.Sum(teamBreaks)));
cp.Add(cp.Minimize(breaks));
//
// Catalyzing constraints
//
// Each team plays home the same number of times as away
for (int i = 0; i < n; i++)
{
cp.Add(cp.Eq(cp.Sum(playHome[i]), nbWeeks / 2));
}
// Breaks must be even for each team
for (int i = 0; i < n; i++)
{
cp.Add(cp.Eq(cp.Modulo(teamBreaks[i], 2), 0));
}
//
// Symmetry breaking constraints
//
// Teams are interchangeable. Fix first week.
// Also breaks reflection symmetry of the whole schedule.
for (int i = 0; i < nbGamesPerWeek; i++)
{
cp.Add(cp.Eq(home[0][i], i * 2));
cp.Add(cp.Eq(away[0][i], i * 2 + 1));
}
// Order of games in each week is arbitrary.
// Break symmetry by forcing an order.
for (int i = 0; i < nbWeeks; i++)
{
for (int j = 1; j < nbGamesPerWeek; j++)
{
cp.Add(cp.Gt(games[i][j], games[i][j - 1]));
}
}
cp.SetParameter(CP.DoubleParam.TimeLimit, 20);
cp.SetParameter(CP.IntParam.LogPeriod, 10000);
IVarSelector varSel = cp.SelectSmallest(cp.VarIndex(allGames));;
IValueSelector valSel = cp.SelectRandomValue();
ISearchPhase phase = cp.SearchPhase(allGames,
cp.IntVarChooser(varSel),
cp.IntValueChooser(valSel));
cp.SetSearchPhases(phase);
cp.StartNewSearch();
while (cp.Next())
{
Console.WriteLine("Solution at {0}", cp.GetValue(breaks));
}
cp.EndSearch();
}
catch (ILOG.Concert.Exception e)
{
Console.WriteLine("Error {0}", e);
}
}
public static IIntExpr MakeScenarioSubmodel(CP cp,
int nbJobs,
int nbMachines,
int[][] machines,
int[][] durations,
IIntervalSequenceVar[] sequences)
{
List<IIntervalVar>[] machinesOps = new List<IIntervalVar>[nbMachines];
String name;
int i,j;
for (j = 0; j < nbMachines; j++)
machinesOps[j] = new List<IIntervalVar>();
IIntExpr[] ends = new IIntExpr[nbJobs];
for (i = 0; i < nbJobs; i++) {
IIntervalVar prec = cp.IntervalVar();
for (j = 0; j < nbMachines; j++) {
name = "J" + i + "_O" + j;
IIntervalVar ti = cp.IntervalVar(durations[i][j], name);
machinesOps[machines[i][j]].Add(ti);
if (j > 0)
cp.Add(cp.EndBeforeStart(prec, ti));
prec = ti;
}
ends[i] = cp.EndOf(prec);
}
for (j = 0; j < nbMachines; j++) {
name = "M" + j;
sequences[j] = cp.IntervalSequenceVar(machinesOps[j].ToArray(), name);
cp.Add(cp.NoOverlap(sequences[j]));
}
return cp.Max(ends);
}