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SatSolverTests.cs
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using System;
using System.Collections.Generic;
using Xunit;
using Google.OrTools.Sat;
namespace Google.OrTools.Tests
{
public class SatSolverTest
{
static IntegerVariableProto NewIntegerVariable(long lb, long ub)
{
IntegerVariableProto var = new IntegerVariableProto();
var.Domain.Add(lb);
var.Domain.Add(ub);
return var;
}
static ConstraintProto NewLinear2(int v1, int v2, long c1, long c2, long lb, long ub)
{
LinearConstraintProto linear = new LinearConstraintProto();
linear.Vars.Add(v1);
linear.Vars.Add(v2);
linear.Coeffs.Add(c1);
linear.Coeffs.Add(c2);
linear.Domain.Add(lb);
linear.Domain.Add(ub);
ConstraintProto ct = new ConstraintProto();
ct.Linear = linear;
return ct;
}
static ConstraintProto NewLinear3(int v1, int v2, int v3, long c1, long c2, long c3, long lb, long ub)
{
LinearConstraintProto linear = new LinearConstraintProto();
linear.Vars.Add(v1);
linear.Vars.Add(v2);
linear.Vars.Add(v3);
linear.Coeffs.Add(c1);
linear.Coeffs.Add(c2);
linear.Coeffs.Add(c3);
linear.Domain.Add(lb);
linear.Domain.Add(ub);
ConstraintProto ct = new ConstraintProto();
ct.Linear = linear;
return ct;
}
static CpObjectiveProto NewMinimize1(int v1, long c1)
{
CpObjectiveProto obj = new CpObjectiveProto();
obj.Vars.Add(v1);
obj.Coeffs.Add(c1);
return obj;
}
static CpObjectiveProto NewMaximize1(int v1, long c1)
{
CpObjectiveProto obj = new CpObjectiveProto();
obj.Vars.Add(-v1 - 1);
obj.Coeffs.Add(c1);
obj.ScalingFactor = -1;
return obj;
}
static CpObjectiveProto NewMaximize2(int v1, int v2, long c1, long c2)
{
CpObjectiveProto obj = new CpObjectiveProto();
obj.Vars.Add(-v1 - 1);
obj.Vars.Add(-v2 - 1);
obj.Coeffs.Add(c1);
obj.Coeffs.Add(c2);
obj.ScalingFactor = -1;
return obj;
}
// CpModelProto
[Fact]
public void SimpleLinearModelProto()
{
CpModelProto model = new CpModelProto();
model.Variables.Add(NewIntegerVariable(-10, 10));
model.Variables.Add(NewIntegerVariable(-10, 10));
model.Variables.Add(NewIntegerVariable(-1000000, 1000000));
model.Constraints.Add(NewLinear2(0, 1, 1, 1, -1000000, 100000));
model.Constraints.Add(NewLinear3(0, 1, 2, 1, 2, -1, 0, 100000));
model.Objective = NewMaximize1(2, 1);
// Console.WriteLine("model = " + model.ToString());
SolveWrapper solve_wrapper = new SolveWrapper();
CpSolverResponse response = solve_wrapper.Solve(model);
Assert.Equal(CpSolverStatus.Optimal, response.Status);
Assert.Equal(30, response.ObjectiveValue);
Assert.Equal(new long[] { 10, 10, 30 }, response.Solution);
// Console.WriteLine("response = " + response.ToString());
}
[Fact]
public void SimpleLinearModelProto2()
{
CpModelProto model = new CpModelProto();
model.Variables.Add(NewIntegerVariable(-10, 10));
model.Variables.Add(NewIntegerVariable(-10, 10));
model.Constraints.Add(NewLinear2(0, 1, 1, 1, -1000000, 100000));
model.Objective = NewMaximize2(0, 1, 1, -2);
// Console.WriteLine("model = " + model.ToString());
SolveWrapper solve_wrapper = new SolveWrapper();
CpSolverResponse response = solve_wrapper.Solve(model);
Assert.Equal(CpSolverStatus.Optimal, response.Status);
Assert.Equal(30, response.ObjectiveValue);
Assert.Equal(new long[] { 10, -10 }, response.Solution);
// Console.WriteLine("response = " + response.ToString());
}
// CpModel
[Fact]
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());
}
[Fact]
public void SimpleLinearModel2()
{
CpModel model = new CpModel();
IntVar v1 = model.NewIntVar(-10, 10, "v1");
IntVar v2 = model.NewIntVar(-10, 10, "v2");
model.AddLinearConstraint(v1 + v2, -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());
}
[Fact]
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());
}
[Fact]
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);
}
[Fact]
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);
}
[Fact]
public void Division()
{
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);
Assert.Equal(CpSolverStatus.Optimal, status);
CpSolverResponse response = solver.Response;
Assert.Equal(3, solver.Value(v1));
Assert.Equal(1, solver.Value(v2));
Assert.Equal(new long[] { 3, 1, 3 }, response.Solution);
Assert.Equal(0, response.ObjectiveValue);
// Console.WriteLine("response = " + reponse.ToString());
}
[Fact]
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.Optimal, 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());
}
[Fact]
public void LargeScalProdLong()
{
CpModel model = new CpModel();
List<IntVar> vars = new List<IntVar>();
List<long> coeffs = new List<long>();
for (int i = 0; i < 100000; ++i)
{
vars.Add(model.NewBoolVar(""));
coeffs.Add(i + 1);
}
var watch = System.Diagnostics.Stopwatch.StartNew();
model.Minimize(LinearExpr.ScalProd(vars, coeffs));
watch.Stop();
var elapsedMs = watch.ElapsedMilliseconds;
Console.WriteLine($"Long: Elapsed time {elapsedMs}");
}
[Fact]
public void LargeScalProdInt()
{
CpModel model = new CpModel();
List<IntVar> vars = new List<IntVar>();
List<int> coeffs = new List<int>();
for (int i = 0; i < 100000; ++i)
{
vars.Add(model.NewBoolVar(""));
coeffs.Add(i);
}
var watch = System.Diagnostics.Stopwatch.StartNew();
model.Minimize(LinearExpr.ScalProd(vars, coeffs));
watch.Stop();
var elapsedMs = watch.ElapsedMilliseconds;
Console.WriteLine($"Int: Elapsed time {elapsedMs}");
}
[Fact]
public void LargeScalProdExpr()
{
CpModel model = new CpModel();
List<LinearExpr> exprs = new List<LinearExpr>();
for (int i = 0; i < 100000; ++i)
{
exprs.Add(model.NewBoolVar("") * i);
}
var watch = System.Diagnostics.Stopwatch.StartNew();
model.Minimize(LinearExpr.Sum(exprs));
watch.Stop();
var elapsedMs = watch.ElapsedMilliseconds;
Console.WriteLine($"Exprs: Elapsed time {elapsedMs}");
}
[Fact]
public void LargeScalProdProto()
{
CpModel model = new CpModel();
List<IntVar> vars = new List<IntVar>();
List<long> coeffs = new List<long>();
for (int i = 0; i < 100000; ++i)
{
vars.Add(model.NewBoolVar(""));
coeffs.Add(i + 1);
}
var watch = System.Diagnostics.Stopwatch.StartNew();
model.Minimize();
for (int i = 0; i < 100000; ++i)
{
model.AddTermToObjective(vars[i], coeffs[i]);
}
watch.Stop();
var elapsedMs = watch.ElapsedMilliseconds;
Console.WriteLine($"Proto: Elapsed time {elapsedMs}");
}
[Fact]
public void ExportModel()
{
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);
Assert.True(model.ExportToFile("test_model_dotnet.pbtxt"));
Console.WriteLine("Model written to file");
}
[Fact]
public void SolveFromString()
{
string model_str = @"
{
""variables"": [
{ ""name"": ""C"", ""domain"": [ ""1"", ""9"" ] },
{ ""name"": ""P"", ""domain"": [ ""0"", ""9"" ] },
{ ""name"": ""I"", ""domain"": [ ""1"", ""9"" ] },
{ ""name"": ""S"", ""domain"": [ ""0"", ""9"" ] },
{ ""name"": ""F"", ""domain"": [ ""1"", ""9"" ] },
{ ""name"": ""U"", ""domain"": [ ""0"", ""9"" ] },
{ ""name"": ""N"", ""domain"": [ ""0"", ""9"" ] },
{ ""name"": ""T"", ""domain"": [ ""1"", ""9"" ] },
{ ""name"": ""R"", ""domain"": [ ""0"", ""9"" ] },
{ ""name"": ""E"", ""domain"": [ ""0"", ""9"" ] }
],
""constraints"": [
{ ""allDiff"": { ""vars"": [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ] } },
{ ""linear"": { ""vars"": [ 6, 5, 9, 4, 3, 7, 8, 2, 0, 1 ], ""coeffs"": [ ""1"", ""0"", ""-1"", ""100"", ""1"", ""-1000"", ""-100"", ""10"", ""10"", ""1"" ], ""domain"": [ ""0"", ""0"" ] } }
]
}";
CpModelProto model = Google.Protobuf.JsonParser.Default.Parse<CpModelProto>(model_str);
SolveWrapper solve_wrapper = new SolveWrapper();
CpSolverResponse response = solve_wrapper.Solve(model);
Console.WriteLine(response);
}
[Fact]
public void CaptureLog() {
Console.WriteLine("CaptureLog test");
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();
solver.StringParameters = "log_search_progress:true log_to_stdout:false";
string log = "";
solver.SetLogCallback(message => log += message + "\n");
solver.Solve(model);
Assert.NotEmpty(log);
Assert.Contains("OPTIMAL", log);
}
}
} // namespace Google.OrTools.Tests