static void Main()
{
// Create the CP-SAT model.
CpModel model = new CpModel();
// Declare our primary variable.
IntVar x = model.NewIntVar(0, 20, "x");
// Create the expression variable and implement the step function
// Note it is not defined for var == 2.
//
// - 3
// -- -- --------- 2
// 1
// -- --- 0
// 0 ================ 20
//
IntVar expr = model.NewIntVar(0, 3, "expr");
// expr == 0 on [5, 6] U [8, 10]
ILiteral b0 = model.NewBoolVar("b0");
model.AddLinearExpressionInDomain(x, Domain.FromValues(new long[] { 5, 6, 8, 9, 10 }))
.OnlyEnforceIf(b0);
model.Add(expr == 0).OnlyEnforceIf(b0);
// expr == 2 on [0, 1] U [3, 4] U [11, 20]
ILiteral b2 = model.NewBoolVar("b2");
model
.AddLinearExpressionInDomain(
x, Domain.FromIntervals(new long[][] { new long[] { 0, 1 }, new long[] { 3, 4 },
new long[] { 11, 20 } }))
.OnlyEnforceIf(b2);
model.Add(expr == 2).OnlyEnforceIf(b2);
// expr == 3 when x == 7
ILiteral b3 = model.NewBoolVar("b3");
model.Add(x == 7).OnlyEnforceIf(b3);
model.Add(expr == 3).OnlyEnforceIf(b3);
// At least one bi is true. (we could use a sum == 1).
model.AddBoolOr(new ILiteral[] { b0, b2, b3 });
// Search for x values in increasing order.
model.AddDecisionStrategy(new IntVar[] { x },
DecisionStrategyProto.Types.VariableSelectionStrategy.ChooseFirst,
DecisionStrategyProto.Types.DomainReductionStrategy.SelectMinValue);
// Create the solver.
CpSolver solver = new CpSolver();
// Force solver to follow the decision strategy exactly.
solver.StringParameters = "search_branching:FIXED_SEARCH";
VarArraySolutionPrinter cb = new VarArraySolutionPrinter(new IntVar[] { x, expr });
solver.SearchAllSolutions(model, cb);
}
public void NegativeSquareVar()
{
CpModel model = new CpModel();
IntVar boolvar = model.NewBoolVar("boolvar");
IntVar x = model.NewIntVar(0, 10, "x");
IntVar delta = model.NewIntVar(-5, 5, "delta");
IntVar squaredDelta = model.NewIntVar(0, 25, "squaredDelta");
model.Add(x == 4).OnlyEnforceIf(boolvar);
model.Add(x == 0).OnlyEnforceIf(boolvar.Not());
model.Add(delta == x - 5);
long[,] tuples = { { -5, 25 }, { -4, 16 }, { -3, 9 }, { -2, 4 }, { -1, 1 }, { 0, 0 },
{ 1, 1 }, { 2, 4 }, { 3, 9 }, { 4, 16 }, { 5, 25 } };
model.AddAllowedAssignments(new IntVar[] { delta, squaredDelta }, tuples);
model.Minimize(squaredDelta);
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
CpSolverResponse response = solver.Response;
Assert.Equal(1, solver.Value(boolvar));
Assert.Equal(4, solver.Value(x));
Assert.Equal(-1, solver.Value(delta));
Assert.Equal(1, solver.Value(squaredDelta));
Assert.Equal(new long[] { 1, 4, -1, 1 }, response.Solution);
Assert.Equal(1.0, response.ObjectiveValue, 6);
}
public void NegativeIntVar()
{
CpModel model = new CpModel();
IntVar boolvar = model.NewBoolVar("boolvar");
IntVar x = model.NewIntVar(0, 10, "x");
IntVar delta = model.NewIntVar(-5, 5, "delta");
IntVar squaredDelta = model.NewIntVar(0, 25, "squaredDelta");
model.Add(x == boolvar * 4);
model.Add(delta == x - 5);
model.AddProdEquality(squaredDelta, new IntVar[] { delta, delta });
model.Minimize(squaredDelta);
// Console.WriteLine("model = " + model.Model.ToString());
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
CpSolverResponse response = solver.Response;
Console.WriteLine("response = " + response.ToString());
Assert.Equal(CpSolverStatus.Optimal, status);
Assert.Equal(1, solver.Value(boolvar));
Assert.Equal(4, solver.Value(x));
Assert.Equal(-1, solver.Value(delta));
Assert.Equal(1, solver.Value(squaredDelta));
Assert.Equal(new long[] { 1, 4, -1, 1 }, response.Solution);
Assert.Equal(1.0, response.ObjectiveValue, 5);
}
static void MinimalCpSatWithTimeLimit()
{
// Creates the model.
CpModel model = new CpModel();
// Creates the variables.
int num_vals = 3;
IntVar x = model.NewIntVar(0, num_vals - 1, "x");
IntVar y = model.NewIntVar(0, num_vals - 1, "y");
IntVar z = model.NewIntVar(0, num_vals - 1, "z");
// Creates the constraints.
model.Add(x != y);
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
// Adds a time limit. Parameters are stored as strings in the solver.
solver.StringParameters = "max_time_in_seconds:10.0";
CpSolverStatus status = solver.Solve(model);
if (status == CpSolverStatus.ModelSat)
{
Console.WriteLine("x = " + solver.Value(x));
Console.WriteLine("y = " + solver.Value(y));
Console.WriteLine("z = " + solver.Value(z));
}
}
static void MinimalCpSat()
{
// Creates the model.
CpModel model = new CpModel();
// Creates the variables.
int num_vals = 3;
IntVar x = model.NewIntVar(0, num_vals - 1, "x");
IntVar y = model.NewIntVar(0, num_vals - 1, "y");
IntVar z = model.NewIntVar(0, num_vals - 1, "z");
// Creates the constraints.
model.Add(x != y);
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
if (status == CpSolverStatus.ModelSat)
{
Console.WriteLine("x = " + solver.Value(x));
Console.WriteLine("y = " + solver.Value(y));
Console.WriteLine("z = " + solver.Value(z));
}
}
static void MinimalCpSatPrintIntermediateSolutions()
{
// Creates the model.
CpModel model = new CpModel();
// Creates the variables.
int num_vals = 3;
IntVar x = model.NewIntVar(0, num_vals - 1, "x");
IntVar y = model.NewIntVar(0, num_vals - 1, "y");
IntVar z = model.NewIntVar(0, num_vals - 1, "z");
// Creates the constraints.
model.Add(x != y);
// Create the objective.
model.Maximize(x + 2 * y + 3 * z);
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
VarArraySolutionPrinterWithObjective cb =
new VarArraySolutionPrinterWithObjective(new IntVar[] { x, y, z });
solver.SearchAllSolutions(model, cb);
Console.WriteLine(String.Format("Number of solutions found: {0}",
cb.SolutionCount()));
}
static void Main()
{
// Creates the model.
// [START model]
CpModel model = new CpModel();
// [END model]
// Creates the variables.
// [START variables]
int num_vals = 3;
IntVar x = model.NewIntVar(0, num_vals - 1, "x");
IntVar y = model.NewIntVar(0, num_vals - 1, "y");
IntVar z = model.NewIntVar(0, num_vals - 1, "z");
// [END variables]
// Adds a different constraint.
// [START constraints]
model.Add(x != y);
// [END constraints]
// Creates a solver and solves the model.
// [START solve]
CpSolver solver = new CpSolver();
VarArraySolutionPrinter cb = new VarArraySolutionPrinter(new IntVar[] { x, y, z });
solver.SearchAllSolutions(model, cb);
// [END solve]
Console.WriteLine(String.Format("Number of solutions found: {0}", cb.SolutionCount()));
}
static void MinimalCpSatPrintIntermediateSolutions()
{
// Creates the model.
CpModel model = new CpModel();
// Creates the variables.
int num_vals = 3;
IntVar x = model.NewIntVar(0, num_vals - 1, 'x');
IntVar y = model.NewIntVar(0, num_vals - 1, 'y');
IntVar z = model.NewIntVar(0, num_vals - 1, 'z');
// Adds a different constraint.
model.Add(x != y);
// Maximizes a linear combination of variables.
model.Maximize(x + 2 * y + 3 * z);
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
VarArraySolutionPrinterWithObjective cb =
new VarArraySolutionPrinterWithObjective(new IntVar[] { x, y, z });
solver.SolveWithSolutionCallback(model, cb);
Console.WriteLine(String.Format('Number of solutions found: {0}',
cb.SolutionCount()));
}
static void TestNegativeSquareVar()
{
CpModel model = new CpModel();
IntVar boolvar = model.NewBoolVar("boolvar");
IntVar x = model.NewIntVar(0, 10, "x");
IntVar delta = model.NewIntVar(-5, 5, "delta");
IntVar squaredDelta = model.NewIntVar(0, 25, "squaredDelta");
model.Add(x == 4).OnlyEnforceIf(boolvar);
model.Add(x == 0).OnlyEnforceIf(boolvar.Not());
model.Add(delta == x - 5);
long[,] tuples = { { -5, 25 }, { -4, 16 }, { -3, 9 }, { -2, 4 }, { -1, 1 }, { 0, 0 },
{ 1, 1 }, { 2, 4 }, { 3, 9 }, { 4, 16 }, { 5, 25 } };
model.AddAllowedAssignments(new IntVar[] { delta, squaredDelta }, tuples);
model.Minimize(squaredDelta);
// Creates the solver and solve.
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
Console.WriteLine(solver.ResponseStats());
}
static void Main()
{
// Creates the model.
// [START model]
CpModel model = new CpModel();
// [END model]
// Creates the variables.
// [START variables]
int num_vals = 3;
IntVar x = model.NewIntVar(0, num_vals - 1, "x");
IntVar y = model.NewIntVar(0, num_vals - 1, "y");
IntVar z = model.NewIntVar(0, num_vals - 1, "z");
// [END variables]
// Adds a different constraint.
// [START constraints]
model.Add(x != y);
// [END constraints]
// Creates a solver and solves the model.
// [START solve]
CpSolver solver = new CpSolver();
VarArraySolutionPrinter cb = new VarArraySolutionPrinter(new IntVar[] { x, y, z });
// Search for all solutions.
solver.StringParameters = "enumerate_all_solutions:true";
// And solve.
solver.Solve(model, cb);
// [END solve]
Console.WriteLine($"Number of solutions found: {cb.SolutionCount()}");
}
public void SimpleLinearModel()
{
CpModel model = new CpModel();
IntVar v1 = model.NewIntVar(-10, 10, "v1");
IntVar v2 = model.NewIntVar(-10, 10, "v2");
IntVar v3 = model.NewIntVar(-100000, 100000, "v3");
model.AddLinearConstraint(v1 + v2, -1000000, 100000);
model.AddLinearConstraint(v1 + 2 * v2 - v3, 0, 100000);
model.Maximize(v3);
Assert.Equal(v1.Domain.FlattenedIntervals(),
new long[] { -10, 10 });
//Console.WriteLine("model = " + model.Model.ToString());
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
Assert.Equal(CpSolverStatus.Optimal, status);
CpSolverResponse response = solver.Response;
Assert.Equal(30, response.ObjectiveValue);
Assert.Equal(new long[] { 10, 10, 30 }, response.Solution);
//Console.WriteLine("response = " + reponse.ToString());
}
static void Main()
{
// Creates the model.
// [START model]
CpModel model = new CpModel();
// [END model]
// Creates the variables.
// [START variables]
int varUpperBound = new int[] { 50, 45, 37 }.Max();
IntVar x = model.NewIntVar(0, varUpperBound, "x");
IntVar y = model.NewIntVar(0, varUpperBound, "y");
IntVar z = model.NewIntVar(0, varUpperBound, "z");
// [END variables]
// Creates the constraints.
// [START constraints]
model.Add(2 * x + 7 * y + 3 * z <= 50);
model.Add(3 * x - 5 * y + 7 * z <= 45);
model.Add(5 * x + 2 * y - 6 * z <= 37);
// [END constraints]
// [START objective]
model.Maximize(2 * x + 2 * y + 3 * z);
// [END objective]
// Creates a solver and solves the model.
// [START solve]
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
// [END solve]
// [START print_solution]
if (status == CpSolverStatus.Optimal || status == CpSolverStatus.Feasible)
{
Console.WriteLine($"Maximum of objective function: {solver.ObjectiveValue}");
Console.WriteLine("x = " + solver.Value(x));
Console.WriteLine("y = " + solver.Value(y));
Console.WriteLine("z = " + solver.Value(z));
}
else
{
Console.WriteLine("No solution found.");
}
// [END print_solution]
// [START statistics]
Console.WriteLine("Statistics");
Console.WriteLine($" conflicts: {solver.NumConflicts()}");
Console.WriteLine($" branches : {solver.NumBranches()}");
Console.WriteLine($" wall time: {solver.WallTime()}s");
// [END statistics]
}
static void Main()
{
long earliness_date = 5;
long earliness_cost = 8;
long lateness_date = 15;
long lateness_cost = 12;
// Create the CP-SAT model.
CpModel model = new CpModel();
// Declare our primary variable.
IntVar x = model.NewIntVar(0, 20, "x");
// Create the expression variable and implement the piecewise linear
// function.
//
// \ /
// \______/
// ed ld
//
long large_constant = 1000;
IntVar expr = model.NewIntVar(0, large_constant, "expr");
// First segment.
IntVar s1 = model.NewIntVar(-large_constant, large_constant, "s1");
model.Add(s1 == earliness_cost * (earliness_date - x));
// Second segment.
IntVar s2 = model.NewConstant(0);
// Third segment.
IntVar s3 = model.NewIntVar(-large_constant, large_constant, "s3");
model.Add(s3 == lateness_cost * (x - lateness_date));
// Link together expr and x through s1, s2, and s3.
model.AddMaxEquality(expr, new IntVar[] { s1, s2, s3 });
// Search for x values in increasing order.
model.AddDecisionStrategy(
new IntVar[] { x },
DecisionStrategyProto.Types.VariableSelectionStrategy.ChooseFirst,
DecisionStrategyProto.Types.DomainReductionStrategy.SelectMinValue);
// Create the solver.
CpSolver solver = new CpSolver();
// Force solver to follow the decision strategy exactly.
solver.StringParameters = "search_branching:FIXED_SEARCH";
VarArraySolutionPrinter cb =
new VarArraySolutionPrinter(new IntVar[] { x, expr });
solver.SearchAllSolutions(model, cb);
}
// [END solution_printer]
static void Main()
{
// Constraint programming engine
// [START model]
CpModel model = new CpModel();
// [START model]
// [START variables]
int BoardSize = 8;
IntVar[] queens = new IntVar[BoardSize];
for (int i = 0; i < BoardSize; ++i)
{
queens[i] = model.NewIntVar(0, BoardSize - 1, $"x{i}");
}
// [END variables]
// Define constraints.
// [START constraints]
// All rows must be different.
model.AddAllDifferent(queens);
// All columns must be different because the indices of queens are all different.
// No two queens can be on the same diagonal.
LinearExpr[] diag1 = new LinearExpr[BoardSize];
LinearExpr[] diag2 = new LinearExpr[BoardSize];
for (int i = 0; i < BoardSize; ++i)
{
diag1[i] = LinearExpr.Affine(queens[i], /*coeff=*/ 1, /*offset=*/ i);
diag2[i] = LinearExpr.Affine(queens[i], /*coeff=*/ 1, /*offset=*/ -i);
}
model.AddAllDifferent(diag1);
model.AddAllDifferent(diag2);
// [END constraints]
// [START solve]
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
SolutionPrinter cb = new SolutionPrinter(queens);
// Search for all solutions.
solver.StringParameters = "enumerate_all_solutions:true";
// And solve.
solver.Solve(model, cb);
// [END solve]
// [START statistics]
Console.WriteLine("Statistics");
Console.WriteLine($" conflicts : {solver.NumConflicts()}");
Console.WriteLine($" branches : {solver.NumBranches()}");
Console.WriteLine($" wall time : {solver.WallTime()} s");
Console.WriteLine($" number of solutions found: {cb.SolutionCount()}");
// [END statistics]
}
static void Main()
{
InitTaskList();
int taskCount = GetTaskCount();
CpModel model = new CpModel();
IntervalVar[] tasks = new IntervalVar[taskCount];
BoolVar[] taskChoosed = new BoolVar[taskCount];
IntVar[] allEnds = new IntVar[GetEndTaskCount()];
int endJobCounter = 0;
foreach (Job j in myJobList)
{
BoolVar[] tmp = new BoolVar[j.AlternativeTasks.Count];
int i = 0;
foreach (Task t in j.AlternativeTasks)
{
long ti = taskIndexes[t.Name];
taskChoosed[ti] = model.NewBoolVar(t.Name + "_choose");
tmp[i++] = taskChoosed[ti];
IntVar start = model.NewIntVar(0, 10000, t.Name + "_start");
IntVar end = model.NewIntVar(0, 10000, t.Name + "_end");
tasks[ti] = model.NewIntervalVar(start, t.Duration, end, t.Name + "_interval");
if (j.Successor == null)
{
allEnds[endJobCounter++] = end;
}
if (!tasksToEquipment.ContainsKey(t.Equipment))
{
tasksToEquipment[t.Equipment] = new List <IntervalVar>();
}
tasksToEquipment[t.Equipment].Add(tasks[ti]);
}
model.AddExactlyOne(tmp);
}
foreach (KeyValuePair <long, List <IntervalVar> > pair in tasksToEquipment)
{
model.AddNoOverlap(pair.Value);
}
IntVar makespan = model.NewIntVar(0, 100000, "makespan");
model.AddMaxEquality(makespan, allEnds);
model.Minimize(makespan);
// Create the solver.
CpSolver solver = new CpSolver();
// Solve the problem.
solver.Solve(model);
Console.WriteLine(solver.ResponseStats());
}
public void Solve()
{
// Creates the model.
CpModel model = new CpModel();
// Creates the variables.
int num_vals = 9;
//Creat the Sudoku grid
IntVar[][] grid = new IntVar[9][];
for (int k = 0; k < 9; k++)
{
grid[k] = new IntVar[9];
}
//get initial sudoku grid and put the 9 possibilities in Empty cells
for (int i = 0; i < 9; i++)
{
for (int j = 0; j < 9; j++)
{
if (Sudoku.getCaseInitialSudoku(i, j) == 0)
{
grid[i][j] = model.NewIntVar(1, num_vals, "C" + i.ToString() + j.ToString());
}
else
{
grid[i][j] = model.NewIntVar(Sudoku.getCaseInitialSudoku(i, j), Sudoku.getCaseInitialSudoku(i, j), "C" + i.ToString() + j.ToString());
}
}
}
// Adds a different constraint.
for (int k = 0; k < 9; k++)
{
//All the ligne might have a different number in each cells
model.AddAllDifferent(GetRow(grid, k));
//All the columns might have a different number in each cells
model.AddAllDifferent(GetColumn(grid, k));
}
//All 9 Regions might have a different number in each cells
for (int region = 0; region < 9; region++)
{
model.AddAllDifferent(GetRegion(grid, region));
}
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
VarArraySolutionPrinter cb = new VarArraySolutionPrinter(grid);
solver.SearchAllSolutions(model, cb);
int[][] values = cb.getValues();
Sudoku.setSudoku(values);
}
static void Main()
{
CpModel model = new CpModel();
// Three weeks.
int horizon = 21;
// Task 0, duration 2.
IntVar start_0 = model.NewIntVar(0, horizon, "start_0");
int duration_0 = 2;
IntVar end_0 = model.NewIntVar(0, horizon, "end_0");
IntervalVar task_0 =
model.NewIntervalVar(start_0, duration_0, end_0, "task_0");
// Task 1, duration 4.
IntVar start_1 = model.NewIntVar(0, horizon, "start_1");
int duration_1 = 4;
IntVar end_1 = model.NewIntVar(0, horizon, "end_1");
IntervalVar task_1 =
model.NewIntervalVar(start_1, duration_1, end_1, "task_1");
// Task 2, duration 3.
IntVar start_2 = model.NewIntVar(0, horizon, "start_2");
int duration_2 = 3;
IntVar end_2 = model.NewIntVar(0, horizon, "end_2");
IntervalVar task_2 =
model.NewIntervalVar(start_2, duration_2, end_2, "task_2");
// Weekends.
IntervalVar weekend_0 = model.NewIntervalVar(5, 2, 7, "weekend_0");
IntervalVar weekend_1 = model.NewIntervalVar(12, 2, 14, "weekend_1");
IntervalVar weekend_2 = model.NewIntervalVar(19, 2, 21, "weekend_2");
// No Overlap constraint.
model.AddNoOverlap(new IntervalVar[] { task_0, task_1, task_2, weekend_0,
weekend_1, weekend_2 });
// Makespan objective.
IntVar obj = model.NewIntVar(0, horizon, "makespan");
model.AddMaxEquality(obj, new IntVar[] { end_0, end_1, end_2 });
model.Minimize(obj);
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
if (status == CpSolverStatus.Optimal)
{
Console.WriteLine("Optimal Schedule Length: " + solver.ObjectiveValue);
Console.WriteLine("Task 0 starts at " + solver.Value(start_0));
Console.WriteLine("Task 1 starts at " + solver.Value(start_1));
Console.WriteLine("Task 2 starts at " + solver.Value(start_2));
}
}
// Configuration for engine / wheels combinations
public void ConfigureSecondDomain(EngineType engine)
{
Console.WriteLine("Engine / Wheels");
CpModel model = new CpModel();
IntVar gas = model.NewBoolVar("gas");
IntVar electric = model.NewBoolVar("electric");
IntVar w0 = model.NewBoolVar("90/45_17'");
IntVar w1 = model.NewBoolVar("160/45 12'");
IntVar w2 = model.NewBoolVar("165/55 15'");
IntVar w3 = model.NewBoolVar("195/65 16'");
IntVar w4 = model.NewBoolVar("255/65 17'");
IntVar w5 = model.NewBoolVar("300/70 20'");
IntVar w6 = model.NewBoolVar("325/65 24'");
model.AddBoolXor(new[] { gas, electric });
model.Add(electric != w1);
model.Add(electric != w2);
model.Add(electric != w3);
model.Add(electric != w4);
model.Add(electric != w5);
model.Add(electric != w6);
model.Add(gas != w0);
CpSolver solver = new CpSolver();
SolutionPrinter cb =
new SolutionPrinter(new IntVar[] { gas, electric,
w0, w1, w2, w3, w4, w5, w6 });
Console.WriteLine(String.Format("Number of solutions found: {0}",
cb.SolutionCount()));
solver.SearchAllSolutions(model, cb);
var secondDomain = cb.FeasibleSolutions();
var wheels = _wheelsService.Get();
if (engine == EngineType.Gas)
{
List <Wheels> feasibleWheels = wheels.FindAll(x => x.type == gas.ShortString());
feasible_wheels_ = feasibleWheels;
}
if (engine == EngineType.Electric)
{
List <Wheels> feasibleWheels = wheels.FindAll(x => x.type == electric.ShortString());
feasible_wheels_ = feasibleWheels;
}
}
// [END solution_printer]
// Solve the CP+IS+FUN==TRUE cryptarithm.
static void Main()
{
// Constraint programming engine
// [START model]
CpModel model = new CpModel();
// [START model]
// [START variables]
int kBase = 10;
IntVar c = model.NewIntVar(1, kBase - 1, "C");
IntVar p = model.NewIntVar(0, kBase - 1, "P");
IntVar i = model.NewIntVar(1, kBase - 1, "I");
IntVar s = model.NewIntVar(0, kBase - 1, "S");
IntVar f = model.NewIntVar(1, kBase - 1, "F");
IntVar u = model.NewIntVar(0, kBase - 1, "U");
IntVar n = model.NewIntVar(0, kBase - 1, "N");
IntVar t = model.NewIntVar(1, kBase - 1, "T");
IntVar r = model.NewIntVar(0, kBase - 1, "R");
IntVar e = model.NewIntVar(0, kBase - 1, "E");
// We need to group variables in a list to use the constraint AllDifferent.
IntVar[] letters = new IntVar[] { c, p, i, s, f, u, n, t, r, e };
// [END variables]
// [START constraints]
// Define constraints.
model.AddAllDifferent(letters);
// CP + IS + FUN = TRUE
model.Add(c * kBase + p + i * kBase + s + f * kBase * kBase + u * kBase + n ==
t * kBase * kBase * kBase + r * kBase * kBase + u * kBase + e);
// [END constraints]
// [START solve]
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
VarArraySolutionPrinter cb = new VarArraySolutionPrinter(letters);
// Search for all solutions.
solver.StringParameters = "enumerate_all_solutions:true";
// And solve.
solver.Solve(model, cb);
// [END solve]
// [START statistics]
Console.WriteLine("Statistics");
Console.WriteLine($" conflicts : {solver.NumConflicts()}");
Console.WriteLine($" branches : {solver.NumBranches()}");
Console.WriteLine($" wall time : {solver.WallTime()} s");
Console.WriteLine($" number of solutions found: {cb.SolutionCount()}");
// [END statistics]
}
public static void Main(string[] args)
{
// -- CREATE THE MODEL --
var model = new CpModel();
// -- SET UP THE DATA --
var jobs = CreateJobsList();
// Number of machines
var machinesCount = 1 + jobs.Max(job => job.Max(task => task.Item1));
// List of machines
var machines = new List <int>();
InitMachinesList(machinesCount, machines);
// Total duration of a single task
var horizon = jobs.Sum(job => job.Sum(task => task.Item2));
// -- ADD VARIABLES TO MODEL --
// Dictionary of all tasks using a tuple of job and task as key
var tasks = new Dictionary <(int, int), Task>();
// List containing each machines' intervals
// Interval is time between tasks
var machineIntervals = new List <List <IntervalVar> >();
InitMachineIntervalsList(machinesCount, machineIntervals);
// Add all variables to the model
AddModelVariables(jobs, model, horizon, tasks, machineIntervals);
// Add all constraints to the model
AddConstraints(machines, model, machineIntervals, jobs, tasks, horizon);
// Solve the model
var solver = new CpSolver();
var status = solver.Solve(model);
// If an optimal solution is found, print it
if (status == CpSolverStatus.Optimal)
{
PrintSolution(
machinesCount,
AssignTasks(machinesCount, jobs, solver, tasks),
solver);
}
}
static void TestSimpleLinearModel2()
{
Console.WriteLine("TestSimpleLinearModel2");
CpModel model = new CpModel();
IntVar v1 = model.NewIntVar(-10, 10, "v1");
IntVar v2 = model.NewIntVar(-10, 10, "v2");
model.AddLinearConstraint(new[] { v1, v2 }, new[] { 1, 1 }, -1000000, 100000);
model.Maximize(v1 - 2 * v2);
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
Check(status == CpSolverStatus.Optimal, "Wrong status after solve");
CheckDoubleEq(30.0, solver.ObjectiveValue, "Wrong solution value");
Console.WriteLine("response = " + solver.Response.ToString());
}
public static void SatVerifier(
string inFileName,
string strResult)
{
string outFile = inFileName.Replace("In", "Out");
string expected = File.ReadAllText(outFile);
Debug.WriteLine($"Solving {Path.GetFileName(outFile)}");
var lines = strResult.Split(TestTools.NewLineChars, StringSplitOptions.RemoveEmptyEntries);
long expCount, varCount;
TestTools.ParseTwoNumbers(lines[0], out expCount, out varCount);
CpModel model = new CpModel();
CpSolver solver = new CpSolver();
solver.StringParameters = "max_time_in_seconds:5.0";
ILiteral[] variables = Enumerable.Range(0, (int)varCount + 1).Select(n => model.NewBoolVar($"x{n}")).ToArray();
List <ILiteral[]> cnf = lines
.Skip(1)
.Select(e => e.Split(TestTools.IgnoreChars, StringSplitOptions.RemoveEmptyEntries)
.Select(s => int.Parse(s))
.Where(v => v != 0)
.Select(v => v > 0 ? variables[v]: variables[-1 * v].Not())
.ToArray())
.ToList();
foreach (var clause in cnf)
{
model.AddBoolOr(clause);
}
var result = solver.Solve(model);
bool bSat = result == CpSolverStatus.Feasible;
Debug.WriteLine($"Solution found: {bSat}");
var bExpectedSat =
expected.Trim(TestTools.IgnoreChars) == "SATISFIABLE";
Assert.AreEqual(bExpectedSat, bSat);
}
public void SimpleLinearModel2()
{
CpModel model = new CpModel();
IntVar v1 = model.NewIntVar(-10, 10, "v1");
IntVar v2 = model.NewIntVar(-10, 10, "v2");
model.AddLinearConstraint(new[] {v1, v2}, new[] {1, 1}, -1000000, 100000);
model.Maximize(v1 - 2 * v2);
//Console.WriteLine("model = " + model.Model.ToString());
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
Assert.Equal(CpSolverStatus.Optimal, status);
CpSolverResponse response = solver.Response;
Assert.Equal(30, response.ObjectiveValue);
Assert.Equal(new long[] {10, -10}, response.Solution);
//Console.WriteLine("response = " + reponse.ToString());
}
static void Main()
{
// Creates the model.
CpModel model = new CpModel();
// Creates the variables.
int num_vals = 3;
IntVar x = model.NewIntVar(0, num_vals - 1, "x");
IntVar y = model.NewIntVar(0, num_vals - 1, "y");
IntVar z = model.NewIntVar(0, num_vals - 1, "z");
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
VarArraySolutionPrinterWithLimit cb = new VarArraySolutionPrinterWithLimit(new IntVar[] { x, y, z }, 5);
solver.SearchAllSolutions(model, cb);
Console.WriteLine(String.Format("Number of solutions found: {0}", cb.SolutionCount()));
}
static void TestDivision()
{
Console.WriteLine("TestDivision");
CpModel model = new CpModel();
IntVar v1 = model.NewIntVar(0, 10, "v1");
IntVar v2 = model.NewIntVar(1, 10, "v2");
model.AddDivisionEquality(3, v1, v2);
Console.WriteLine(model.Model);
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
Check(status == CpSolverStatus.Feasible, "Wrong status after solve");
Console.WriteLine("v1 = {0}", solver.Value(v1));
Console.WriteLine("v2 = {0}", solver.Value(v2));
}
public void SolverTest(bool callGC)
{
CpModel model = new CpModel();
int num_vals = 3;
IntVar x = model.NewIntVar(0, num_vals - 1, "x");
IntVar y = model.NewIntVar(0, num_vals - 1, "y");
IntVar z = model.NewIntVar(0, num_vals - 1, "z");
model.Add(x != y);
CpSolver solver = new CpSolver();
if (callGC)
{
GC.Collect();
}
CpSolverStatus status = solver.Solve(model);
}
static void TestSimpleLinearModel3()
{
Console.WriteLine("TestSimpleLinearModel3");
CpModel model = new CpModel();
IntVar v1 = model.NewIntVar(-10, 10, "v1");
IntVar v2 = model.NewIntVar(-10, 10, "v2");
model.Add(-100000 <= v1 + 2 * v2 <= 100000);
model.Minimize(v1 - 2 * v2);
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
Check(status == CpSolverStatus.Optimal, "Wrong status after solve");
CheckDoubleEq(-30.0, solver.ObjectiveValue, "Wrong solution value");
CheckLongEq(-10, solver.Value(v1), "Wrong value");
CheckLongEq(10, solver.Value(v2), "Wrong value");
CheckLongEq(-30, solver.Value(v1 - 2 * v2), "Wrong value");
}
public void Modulo()
{
CpModel model = new CpModel();
IntVar v1 = model.NewIntVar(1, 10, "v1");
IntVar v2 = model.NewIntVar(1, 10, "v2");
model.AddModuloEquality(3, v1, v2);
//Console.WriteLine(model.Model);
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
Assert.Equal(CpSolverStatus.Feasible, status);
CpSolverResponse response = solver.Response;
Assert.Equal(3, solver.Value(v1));
Assert.Equal(4, solver.Value(v2));
Assert.Equal(new long[] {3, 4, 3}, response.Solution);
Assert.Equal(0, response.ObjectiveValue);
//Console.WriteLine("response = " + reponse.ToString());
}
static void Main()
{
// Creates the model.
// [START model]
CpModel model = new CpModel();
// [END model]
// Creates the variables.
// [START variables]
int num_vals = 3;
IntVar x = model.NewIntVar(0, num_vals - 1, "x");
IntVar y = model.NewIntVar(0, num_vals - 1, "y");
IntVar z = model.NewIntVar(0, num_vals - 1, "z");
// [END variables]
// Creates the constraints.
// [START constraints]
model.Add(x != y);
// [END constraints]
// Creates a solver and solves the model.
// [START solve]
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
// [END solve]
// [START print_solution]
if (status == CpSolverStatus.Optimal || status == CpSolverStatus.Feasible)
{
Console.WriteLine("x = " + solver.Value(x));
Console.WriteLine("y = " + solver.Value(y));
Console.WriteLine("z = " + solver.Value(z));
}
else
{
Console.WriteLine("No solution found.");
}
// [END print_solution]
}
public void SimpleLinearModel3()
{
CpModel model = new CpModel();
IntVar v1 = model.NewIntVar(-10, 10, "v1");
IntVar v2 = model.NewIntVar(-10, 10, "v2");
model.Add(-100000 <= v1 + 2 * v2 <= 100000);
model.Minimize(v1 - 2 * v2);
//Console.WriteLine("model = " + model.Model.ToString());
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
Assert.Equal(CpSolverStatus.Optimal, status);
CpSolverResponse response = solver.Response;
Assert.Equal(-10, solver.Value(v1));
Assert.Equal(10, solver.Value(v2));
Assert.Equal(new long[] {-10, 10}, response.Solution);
Assert.Equal(-30, solver.Value(v1 - 2 * v2));
Assert.Equal(-30, response.ObjectiveValue);
//Console.WriteLine("response = " + reponse.ToString());
}
