607 lines
22 KiB
C#
607 lines
22 KiB
C#
// Copyright 2010-2021 Google LLC
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
//
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
|
|
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 = " + response.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 = " + response.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 = " + response.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.AddMultiplicationEquality(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();
|
|
BoolVar 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 }).AddTuples(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 }, response.Solution);
|
|
Assert.Equal(0, response.ObjectiveValue);
|
|
// Console.WriteLine("response = " + response.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 }, response.Solution);
|
|
Assert.Equal(0, response.ObjectiveValue);
|
|
// Console.WriteLine("response = " + response.ToString());
|
|
}
|
|
|
|
[Fact]
|
|
public void LargeWeightedSumLong()
|
|
{
|
|
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.WeightedSum(vars, coeffs));
|
|
watch.Stop();
|
|
var elapsedMs = watch.ElapsedMilliseconds;
|
|
Console.WriteLine($"Long: Elapsed time {elapsedMs}");
|
|
}
|
|
|
|
[Fact]
|
|
public void LargeWeightedSumInt()
|
|
{
|
|
CpModel model = new CpModel();
|
|
List<IntVar> vars = new List<IntVar>();
|
|
List<int> coeffs = new List<int>();
|
|
|
|
for (int i = 0; i < 100000; ++i)
|
|
{
|
|
vars.Add(model.NewBoolVar(""));
|
|
coeffs.Add(i);
|
|
}
|
|
|
|
var watch = System.Diagnostics.Stopwatch.StartNew();
|
|
model.Minimize(LinearExpr.WeightedSum(vars, coeffs));
|
|
watch.Stop();
|
|
var elapsedMs = watch.ElapsedMilliseconds;
|
|
Console.WriteLine($"Int: Elapsed time {elapsedMs}");
|
|
}
|
|
|
|
[Fact]
|
|
public void LargeWeightedSumExpr()
|
|
{
|
|
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($"Exprs: Elapsed time {elapsedMs}");
|
|
}
|
|
|
|
[Fact]
|
|
public void LargeWeightedSumBuilder()
|
|
{
|
|
CpModel model = new CpModel();
|
|
List<IntVar> vars = new List<IntVar>();
|
|
List<long> coeffs = new List<long>();
|
|
|
|
for (int i = 0; i < 100000; ++i)
|
|
{
|
|
vars.Add(model.NewBoolVar(""));
|
|
coeffs.Add(i + 1);
|
|
}
|
|
|
|
var watch = System.Diagnostics.Stopwatch.StartNew();
|
|
LinearExprBuilder obj = LinearExpr.NewBuilder();
|
|
for (int i = 0; i < 100000; ++i)
|
|
{
|
|
obj.AddTerm(vars[i], coeffs[i]);
|
|
}
|
|
model.Minimize(obj);
|
|
watch.Stop();
|
|
var elapsedMs = watch.ElapsedMilliseconds;
|
|
Console.WriteLine($"Proto: Elapsed time {elapsedMs}");
|
|
}
|
|
|
|
[Fact]
|
|
public void LinearExprStaticCompileTest()
|
|
{
|
|
Console.WriteLine("LinearExprStaticCompileTest");
|
|
CpModel model = new CpModel();
|
|
IntVar v1 = model.NewIntVar(-10, 10, "v1");
|
|
IntVar v2 = model.NewIntVar(-10, 10, "v2");
|
|
BoolVar b1 = model.NewBoolVar("b1");
|
|
BoolVar b2 = model.NewBoolVar("b2");
|
|
long[] c1 = new long[] { 2L, 4L };
|
|
int[] c2 = new int[] { 2, 4 };
|
|
LinearExpr e1 = LinearExpr.Sum(new IntVar[] { v1, v2 });
|
|
Console.WriteLine(e1.ToString());
|
|
LinearExpr e2 = LinearExpr.Sum(new ILiteral[] { b1, b2 });
|
|
Console.WriteLine(e2.ToString());
|
|
LinearExpr e3 = LinearExpr.Sum(new BoolVar[] { b1, b2 });
|
|
Console.WriteLine(e3.ToString());
|
|
LinearExpr e4 = LinearExpr.WeightedSum(new IntVar[] { v1, v2 }, c1);
|
|
Console.WriteLine(e4.ToString());
|
|
LinearExpr e5 = LinearExpr.WeightedSum(new ILiteral[] { b1, b2 }, c1);
|
|
Console.WriteLine(e5.ToString());
|
|
LinearExpr e6 = LinearExpr.WeightedSum(new BoolVar[] { b1, b2 }, c1);
|
|
Console.WriteLine(e6.ToString());
|
|
LinearExpr e7 = LinearExpr.WeightedSum(new IntVar[] { v1, v2 }, c2);
|
|
Console.WriteLine(e7.ToString());
|
|
LinearExpr e8 = LinearExpr.WeightedSum(new ILiteral[] { b1, b2 }, c2);
|
|
Console.WriteLine(e8.ToString());
|
|
LinearExpr e9 = LinearExpr.WeightedSum(new BoolVar[] { b1, b2 }, c2);
|
|
Console.WriteLine(e9.ToString());
|
|
}
|
|
|
|
[Fact]
|
|
public void LinearExprBuilderCompileTest()
|
|
{
|
|
Console.WriteLine("LinearExprBuilderCompileTest");
|
|
CpModel model = new CpModel();
|
|
IntVar v1 = model.NewIntVar(-10, 10, "v1");
|
|
IntVar v2 = model.NewIntVar(-10, 10, "v2");
|
|
BoolVar b1 = model.NewBoolVar("b1");
|
|
BoolVar b2 = model.NewBoolVar("b2");
|
|
long[] c1 = new long[] { 2L, 4L };
|
|
int[] c2 = new int[] { 2, 4 };
|
|
LinearExpr e1 = LinearExpr.NewBuilder().AddSum(new IntVar[] { v1, v2 });
|
|
Console.WriteLine(e1.ToString());
|
|
LinearExpr e2 = LinearExpr.NewBuilder().AddSum(new ILiteral[] { b1, b2 });
|
|
Console.WriteLine(e2.ToString());
|
|
LinearExpr e3 = LinearExpr.NewBuilder().AddSum(new BoolVar[] { b1, b2 });
|
|
Console.WriteLine(e3.ToString());
|
|
LinearExpr e4 = LinearExpr.NewBuilder().AddWeightedSum(new IntVar[] { v1, v2 }, c1);
|
|
Console.WriteLine(e4.ToString());
|
|
LinearExpr e5 = LinearExpr.NewBuilder().AddWeightedSum(new ILiteral[] { b1, b2 }, c1);
|
|
Console.WriteLine(e5.ToString());
|
|
LinearExpr e6 = LinearExpr.NewBuilder().AddWeightedSum(new BoolVar[] { b1, b2 }, c1);
|
|
Console.WriteLine(e6.ToString());
|
|
LinearExpr e7 = LinearExpr.NewBuilder().AddWeightedSum(new IntVar[] { v1, v2 }, c2);
|
|
Console.WriteLine(e7.ToString());
|
|
LinearExpr e8 = LinearExpr.NewBuilder().AddWeightedSum(new ILiteral[] { b1, b2 }, c2);
|
|
Console.WriteLine(e8.ToString());
|
|
LinearExpr e9 = LinearExpr.NewBuilder().AddWeightedSum(new BoolVar[] { b1, b2 }, c2);
|
|
Console.WriteLine(e9.ToString());
|
|
LinearExpr e10 = LinearExpr.NewBuilder().Add(v1);
|
|
Console.WriteLine(e10.ToString());
|
|
LinearExpr e11 = LinearExpr.NewBuilder().Add(b1);
|
|
Console.WriteLine(e11.ToString());
|
|
LinearExpr e12 = LinearExpr.NewBuilder().Add(b1.Not());
|
|
Console.WriteLine(e12.ToString());
|
|
LinearExpr e13 = LinearExpr.NewBuilder().AddTerm(v1, -1);
|
|
Console.WriteLine(e13.ToString());
|
|
LinearExpr e14 = LinearExpr.NewBuilder().AddTerm(b1, -1);
|
|
Console.WriteLine(e14.ToString());
|
|
LinearExpr e15 = LinearExpr.NewBuilder().AddTerm(b1.Not(), -2);
|
|
Console.WriteLine(e15.ToString());
|
|
}
|
|
|
|
[Fact]
|
|
public void LinearExprIntVarOperatorTest()
|
|
{
|
|
Console.WriteLine("LinearExprIntVarOperatorTest");
|
|
CpModel model = new CpModel();
|
|
IntVar v = model.NewIntVar(-10, 10, "v");
|
|
LinearExpr e = v * 2;
|
|
Console.WriteLine(e);
|
|
e = 2 * v;
|
|
Console.WriteLine(e);
|
|
e = v + 2;
|
|
Console.WriteLine(e);
|
|
e = 2 + v;
|
|
Console.WriteLine(e);
|
|
e = v;
|
|
Console.WriteLine(e);
|
|
e = -v;
|
|
Console.WriteLine(e);
|
|
e = 1 - v;
|
|
Console.WriteLine(e);
|
|
e = v - 1;
|
|
Console.WriteLine(e);
|
|
}
|
|
|
|
[Fact]
|
|
public void LinearExprBoolVarOperatorTest()
|
|
{
|
|
Console.WriteLine("LinearExprBoolVarOperatorTest");
|
|
CpModel model = new CpModel();
|
|
BoolVar v = model.NewBoolVar("v");
|
|
LinearExpr e = v * 2;
|
|
Console.WriteLine(e);
|
|
e = 2 * v;
|
|
Console.WriteLine(e);
|
|
e = v + 2;
|
|
Console.WriteLine(e);
|
|
e = 2 + v;
|
|
Console.WriteLine(e);
|
|
e = v;
|
|
Console.WriteLine(e);
|
|
e = -v;
|
|
Console.WriteLine(e);
|
|
e = 1 - v;
|
|
Console.WriteLine(e);
|
|
e = v - 1;
|
|
Console.WriteLine(e);
|
|
}
|
|
|
|
[Fact]
|
|
public void LinearExprNotBoolVarOperatorTest()
|
|
{
|
|
Console.WriteLine("LinearExprBoolVarNotOperatorTest");
|
|
CpModel model = new CpModel();
|
|
ILiteral v = model.NewBoolVar("v");
|
|
LinearExpr e = v.NotAsExpr() * 2;
|
|
Console.WriteLine(e);
|
|
e = 2 * v.NotAsExpr();
|
|
Console.WriteLine(e);
|
|
e = v.NotAsExpr() + 2;
|
|
Console.WriteLine(e);
|
|
e = 2 + v.NotAsExpr();
|
|
Console.WriteLine(e);
|
|
e = v.NotAsExpr();
|
|
Console.WriteLine(e);
|
|
e = -v.NotAsExpr();
|
|
Console.WriteLine(e);
|
|
e = 1 - v.NotAsExpr();
|
|
Console.WriteLine(e);
|
|
e = v.NotAsExpr() - 1;
|
|
Console.WriteLine(e);
|
|
}
|
|
[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"": { ""exprs"": [
|
|
{ ""vars"": [""0""], ""coeffs"": [""1""] },
|
|
{ ""vars"": [""1""], ""coeffs"": [""1""] },
|
|
{ ""vars"": [""2""], ""coeffs"": [""1""] },
|
|
{ ""vars"": [""3""], ""coeffs"": [""1""] },
|
|
{ ""vars"": [""4""], ""coeffs"": [""1""] },
|
|
{ ""vars"": [""5""], ""coeffs"": [""1""] },
|
|
{ ""vars"": [""6""], ""coeffs"": [""1""] },
|
|
{ ""vars"": [""7""], ""coeffs"": [""1""] },
|
|
{ ""vars"": [""8""], ""coeffs"": [""1""] },
|
|
{ ""vars"": [""9""], ""coeffs"": [""1""] } ] } },
|
|
{ ""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);
|
|
}
|
|
|
|
[Fact]
|
|
public void TestInterval()
|
|
{
|
|
Console.WriteLine("TestInterval test");
|
|
CpModel model = new CpModel();
|
|
IntVar v = model.NewIntVar(-10, 10, "v");
|
|
IntervalVar i = model.NewFixedSizeIntervalVar(v, 3, "i");
|
|
Assert.Equal("v", i.StartExpr().ToString());
|
|
Assert.Equal("3", i.SizeExpr().ToString());
|
|
Assert.Equal("v + 3", i.EndExpr().ToString());
|
|
}
|
|
}
|
|
} // namespace Google.OrTools.Tests
|