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add C# sat code samples in ortools/sat/samples; remove old code_samples_sat.* files

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Laurent Perron
2018-07-17 14:00:18 -07:00
parent 9380710b82
commit 0152168fb7
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examples/cpp/code_samples_sat.cc
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// Copyright 2010-2017 Google
// 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.
#include "ortools/base/commandlineflags.h"
#include "ortools/base/logging.h"
#include "ortools/base/timer.h"
#include "ortools/sat/cp_model.pb.h"
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/cp_model_utils.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
namespace operations_research {
namespace sat {
void CodeSample() {
CpModelProto cp_model;
auto new_boolean_variable = [&cp_model]() {
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(0);
var->add_domain(1);
return index;
};
const int x = new_boolean_variable();
LOG(INFO) << x;
}
void LiteralSample() {
CpModelProto cp_model;
auto new_boolean_variable = [&cp_model]() {
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(0);
var->add_domain(1);
return index;
};
const int x = new_boolean_variable();
const int not_x = NegatedRef(x);
LOG(INFO) << "x = " << x << ", not(x) = " << not_x;
}
void BoolOrSample() {
CpModelProto cp_model;
auto new_boolean_variable = [&cp_model]() {
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(0);
var->add_domain(1);
return index;
};
auto add_bool_or = [&cp_model](const std::vector<int>& literals) {
BoolArgumentProto* const bool_or =
cp_model.add_constraints()->mutable_bool_or();
for (const int lit : literals) {
bool_or->add_literals(lit);
}
};
const int x = new_boolean_variable();
const int y = new_boolean_variable();
add_bool_or({x, NegatedRef(y)});
}
void ReifiedSample() {
CpModelProto cp_model;
auto new_boolean_variable = [&cp_model]() {
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(0);
var->add_domain(1);
return index;
};
auto add_bool_or = [&cp_model](const std::vector<int>& literals) {
BoolArgumentProto* const bool_or =
cp_model.add_constraints()->mutable_bool_or();
for (const int lit : literals) {
bool_or->add_literals(lit);
}
};
auto add_reified_bool_and = [&cp_model](const std::vector<int>& literals,
const int literal) {
ConstraintProto* const ct = cp_model.add_constraints();
ct->add_enforcement_literal(literal);
for (const int lit : literals) {
ct->mutable_bool_and()->add_literals(lit);
}
};
const int x = new_boolean_variable();
const int y = new_boolean_variable();
const int b = new_boolean_variable();
// First version using a half-reified bool and.
add_reified_bool_and({x, NegatedRef(y)}, b);
// Second version using bool or.
add_bool_or({NegatedRef(b), x});
add_bool_or({NegatedRef(b), NegatedRef(y)});
}
void RabbitsAndPheasants() {
CpModelProto cp_model;
// Trivial model with just one variable and no constraint.
auto new_variable = [&cp_model](int64 lb, int64 ub) {
CHECK_LE(lb, ub);
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(lb);
var->add_domain(ub);
return index;
};
auto add_linear_constraint = [&cp_model](const std::vector<int>& vars,
const std::vector<int64>& coeffs,
int64 lb, int64 ub) {
LinearConstraintProto* const lin =
cp_model.add_constraints()->mutable_linear();
for (const int v : vars) {
lin->add_vars(v);
}
for (const int64 c : coeffs) {
lin->add_coeffs(c);
}
lin->add_domain(lb);
lin->add_domain(ub);
};
// Creates variables.
const int r = new_variable(0, 100);
const int p = new_variable(0, 100);
// 20 heads.
add_linear_constraint({r, p}, {1, 1}, 20, 20);
// 56 legs.
add_linear_constraint({r, p}, {4, 2}, 56, 56);
// Solving part.
Model model;
LOG(INFO) << CpModelStats(cp_model);
const CpSolverResponse response = SolveCpModel(cp_model, &model);
LOG(INFO) << CpSolverResponseStats(response);
if (response.status() == CpSolverStatus::FEASIBLE) {
// Get the value of x in the solution.
LOG(INFO) << response.solution(r) << " rabbits, and "
<< response.solution(p) << " pheasants";
}
}
void BinpackingProblem() {
// Data.
const int kBinCapacity = 100;
const int kSlackCapacity = 20;
const int kNumBins = 10;
const std::vector<std::vector<int>> items = {
{20, 12}, {15, 12}, {30, 8}, {45, 5}};
const int num_items = items.size();
// Model.
CpModelProto cp_model;
// Helpers.
auto new_variable = [&cp_model](int64 lb, int64 ub) {
CHECK_LE(lb, ub);
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(lb);
var->add_domain(ub);
return index;
};
auto add_linear_constraint = [&cp_model](const std::vector<int>& vars,
const std::vector<int64>& coeffs,
int64 lb, int64 ub) {
LinearConstraintProto* const lin =
cp_model.add_constraints()->mutable_linear();
for (const int v : vars) {
lin->add_vars(v);
}
for (const int64 c : coeffs) {
lin->add_coeffs(c);
}
lin->add_domain(lb);
lin->add_domain(ub);
};
auto add_reified_variable_bounds = [&cp_model](int var, int64 lb, int64 ub,
int lit) {
ConstraintProto* const ct = cp_model.add_constraints();
ct->add_enforcement_literal(lit);
LinearConstraintProto* const lin = ct->mutable_linear();
lin->add_vars(var);
lin->add_coeffs(1);
lin->add_domain(lb);
lin->add_domain(ub);
};
auto maximize = [&cp_model](const std::vector<int>& vars) {
CpObjectiveProto* const obj = cp_model.mutable_objective();
for (const int v : vars) {
obj->add_vars(v);
obj->add_coeffs(-1); // Maximize.
}
obj->set_scaling_factor(-1.0); // Maximize.
};
// Main variables.
std::vector<std::vector<int>> x(num_items);
for (int i = 0; i < num_items; ++i) {
const int num_copies = items[i][1];
for (int b = 0; b < kNumBins; ++b) {
x[i].push_back(new_variable(0, num_copies));
}
}
// Load variables.
std::vector<int> load(kNumBins);
for (int b = 0; b < kNumBins; ++b) {
load[b] = new_variable(0, kBinCapacity);
}
// Slack variables.
std::vector<int> slack(kNumBins);
for (int b = 0; b < kNumBins; ++b) {
slack[b] = new_variable(0, 1);
}
// Links load and x.
for (int b = 0; b < kNumBins; ++b) {
std::vector<int> vars;
std::vector<int64> coeffs;
vars.push_back(load[b]);
coeffs.push_back(-1);
for (int i = 0; i < num_items; ++i) {
vars.push_back(x[i][b]);
coeffs.push_back(items[i][0]);
}
add_linear_constraint(vars, coeffs, 0, 0);
}
// Place all items.
for (int i = 0; i < num_items; ++i) {
std::vector<int> vars;
std::vector<int64> coeffs;
for (int b = 0; b < kNumBins; ++b) {
vars.push_back(x[i][b]);
coeffs.push_back(1);
}
add_linear_constraint(vars, coeffs, items[i][1], items[i][1]);
}
// Links load and slack through an equivalence relation.
const int safe_capacity = kBinCapacity - kSlackCapacity;
for (int b = 0; b < kNumBins; ++b) {
// slack[b] => load[b] <= safe_capacity.
add_reified_variable_bounds(load[b], kint64min, safe_capacity, slack[b]);
// not(slack[b]) => load[b] > safe_capacity.
add_reified_variable_bounds(load[b], safe_capacity + 1, kint64max,
NegatedRef(slack[b]));
}
// Maximize sum of slacks.
maximize(slack);
// Solving part.
Model model;
LOG(INFO) << CpModelStats(cp_model);
const CpSolverResponse response = SolveCpModel(cp_model, &model);
LOG(INFO) << CpSolverResponseStats(response);
}
void IntervalSample() {
CpModelProto cp_model;
const int kHorizon = 100;
auto new_variable = [&cp_model](int64 lb, int64 ub) {
CHECK_LE(lb, ub);
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(lb);
var->add_domain(ub);
return index;
};
auto new_constant = [&cp_model, &new_variable](int64 v) {
return new_variable(v, v);
};
auto new_interval = [&cp_model](int start, int duration, int end) {
const int index = cp_model.constraints_size();
IntervalConstraintProto* const interval =
cp_model.add_constraints()->mutable_interval();
interval->set_start(start);
interval->set_size(duration);
interval->set_end(end);
return index;
};
const int start_var = new_variable(0, kHorizon);
const int duration_var = new_constant(10);
const int end_var = new_variable(0, kHorizon);
const int interval_var = new_interval(start_var, duration_var, end_var);
LOG(INFO) << "start_var = " << start_var
<< ", duration_var = " << duration_var << ", end_var = " << end_var
<< ", interval_var = " << interval_var;
}
void OptionalIntervalSample() {
CpModelProto cp_model;
const int kHorizon = 100;
auto new_variable = [&cp_model](int64 lb, int64 ub) {
CHECK_LE(lb, ub);
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(lb);
var->add_domain(ub);
return index;
};
auto new_constant = [&cp_model, &new_variable](int64 v) {
return new_variable(v, v);
};
auto new_optional_interval = [&cp_model](int start, int duration, int end,
int presence) {
const int index = cp_model.constraints_size();
ConstraintProto* const ct = cp_model.add_constraints();
ct->add_enforcement_literal(presence);
IntervalConstraintProto* const interval = ct->mutable_interval();
interval->set_start(start);
interval->set_size(duration);
interval->set_end(end);
return index;
};
const int start_var = new_variable(0, kHorizon);
const int duration_var = new_constant(10);
const int end_var = new_variable(0, kHorizon);
const int presence_var = new_variable(0, 1);
const int interval_var =
new_optional_interval(start_var, duration_var, end_var, presence_var);
LOG(INFO) << "start_var = " << start_var
<< ", duration_var = " << duration_var << ", end_var = " << end_var
<< ", presence_var = " << presence_var
<< ", interval_var = " << interval_var;
}
void SimpleSolve() {
CpModelProto cp_model;
// Trivial model with just one variable and no constraint.
auto new_variable = [&cp_model](int64 lb, int64 ub) {
CHECK_LE(lb, ub);
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(lb);
var->add_domain(ub);
return index;
};
const int x = new_variable(0, 3);
// Solving part.
Model model;
LOG(INFO) << CpModelStats(cp_model);
const CpSolverResponse response = SolveCpModel(cp_model, &model);
LOG(INFO) << CpSolverResponseStats(response);
if (response.status() == CpSolverStatus::FEASIBLE) {
// Get the value of x in the solution.
const int64 value_x = response.solution(x);
LOG(INFO) << "x = " << value_x;
}
}
void SolveWithTimeLimit() {
CpModelProto cp_model;
// Trivial model with just one variable and no constraint.
auto new_variable = [&cp_model](int64 lb, int64 ub) {
CHECK_LE(lb, ub);
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(lb);
var->add_domain(ub);
return index;
};
const int x = new_variable(0, 3);
// Solving part.
Model model;
// Sets a time limit of 10 seconds.
SatParameters parameters;
parameters.set_max_time_in_seconds(10.0);
model.Add(NewSatParameters(parameters));
// Solve.
LOG(INFO) << CpModelStats(cp_model);
const CpSolverResponse response = SolveCpModel(cp_model, &model);
LOG(INFO) << CpSolverResponseStats(response);
if (response.status() == CpSolverStatus::FEASIBLE) {
// Get the value of x in the solution.
const int64 value_x = response.solution(x);
LOG(INFO) << "value_x = " << value_x;
}
}
void MinimalSatPrintIntermediateSolutions() {
CpModelProto cp_model;
auto new_variable = [&cp_model](int64 lb, int64 ub) {
CHECK_LE(lb, ub);
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(lb);
var->add_domain(ub);
return index;
};
auto add_different = [&cp_model](const int left_var, const int right_var) {
LinearConstraintProto* const lin =
cp_model.add_constraints()->mutable_linear();
lin->add_vars(left_var);
lin->add_coeffs(1);
lin->add_vars(right_var);
lin->add_coeffs(-1);
lin->add_domain(kint64min);
lin->add_domain(-1);
lin->add_domain(1);
lin->add_domain(kint64max);
};
auto maximize = [&cp_model](const std::vector<int>& vars,
const std::vector<int64>& coeffs) {
CpObjectiveProto* const obj = cp_model.mutable_objective();
for (const int v : vars) {
obj->add_vars(v);
}
for (const int64 c : coeffs) {
obj->add_coeffs(-c); // Maximize.
}
obj->set_scaling_factor(-1.0); // Maximize.
};
const int kNumVals = 3;
const int x = new_variable(0, kNumVals - 1);
const int y = new_variable(0, kNumVals - 1);
const int z = new_variable(0, kNumVals - 1);
add_different(x, y);
maximize({x, y, z}, {1, 2, 3});
Model model;
int num_solutions = 0;
model.Add(NewFeasibleSolutionObserver([&](const CpSolverResponse& r) {
LOG(INFO) << "Solution " << num_solutions;
LOG(INFO) << " objective value = " << r.objective_value();
LOG(INFO) << " x = " << r.solution(x);
LOG(INFO) << " y = " << r.solution(y);
LOG(INFO) << " z = " << r.solution(z);
num_solutions++;
}));
const CpSolverResponse response = SolveCpModel(cp_model, &model);
LOG(INFO) << "Number of solutions found: " << num_solutions;
}
void MinimalSatSearchForAllSolutions() {
CpModelProto cp_model;
auto new_variable = [&cp_model](int64 lb, int64 ub) {
CHECK_LE(lb, ub);
const int index = cp_model.variables_size();
IntegerVariableProto* const var = cp_model.add_variables();
var->add_domain(lb);
var->add_domain(ub);
return index;
};
auto add_different = [&cp_model](const int left_var, const int right_var) {
LinearConstraintProto* const lin =
cp_model.add_constraints()->mutable_linear();
lin->add_vars(left_var);
lin->add_coeffs(1);
lin->add_vars(right_var);
lin->add_coeffs(-1);
lin->add_domain(kint64min);
lin->add_domain(-1);
lin->add_domain(1);
lin->add_domain(kint64max);
};
const int kNumVals = 3;
const int x = new_variable(0, kNumVals - 1);
const int y = new_variable(0, kNumVals - 1);
const int z = new_variable(0, kNumVals - 1);
add_different(x, y);
Model model;
// Tell the solver to enumerate all solutions.
SatParameters parameters;
parameters.set_enumerate_all_solutions(true);
model.Add(NewSatParameters(parameters));
int num_solutions = 0;
model.Add(NewFeasibleSolutionObserver([&](const CpSolverResponse& r) {
LOG(INFO) << "Solution " << num_solutions;
LOG(INFO) << " x = " << r.solution(x);
LOG(INFO) << " y = " << r.solution(y);
LOG(INFO) << " z = " << r.solution(z);
num_solutions++;
}));
const CpSolverResponse response = SolveCpModel(cp_model, &model);
LOG(INFO) << "Number of solutions found: " << num_solutions;
}
} // namespace sat
} // namespace operations_research
int main() {
LOG(INFO) << "--- CodeSample ---";
operations_research::sat::CodeSample();
LOG(INFO) << "--- LiteralSample ---";
operations_research::sat::LiteralSample();
LOG(INFO) << "--- BoolOrSample ---";
operations_research::sat::BoolOrSample();
LOG(INFO) << "--- ReifiedSample ---";
operations_research::sat::ReifiedSample();
LOG(INFO) << "--- RabbitsAndPheasants ---";
operations_research::sat::RabbitsAndPheasants();
LOG(INFO) << "--- BinpackingProblem ---";
operations_research::sat::BinpackingProblem();
LOG(INFO) << "--- IntervalSample ---";
operations_research::sat::IntervalSample();
LOG(INFO) << "--- OptionalIntervalSample ---";
operations_research::sat::OptionalIntervalSample();
LOG(INFO) << "--- SimpleSolve ---";
operations_research::sat::SimpleSolve();
LOG(INFO) << "--- SolveWithTimeLimit ---";
operations_research::sat::SolveWithTimeLimit();
LOG(INFO) << "--- MinimalSatPrintIntermediateSolutions ---";
operations_research::sat::MinimalSatPrintIntermediateSolutions();
LOG(INFO) << "--- MinimalSatSearchForAllSolutions ---";
operations_research::sat::MinimalSatSearchForAllSolutions();
return EXIT_SUCCESS;
}

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examples/dotnet/csharp-netfx/code_samples_sat.cs
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// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class VarArraySolutionPrinter : CpSolverSolutionCallback
{
public VarArraySolutionPrinter(IntVar[] variables)
{
variables_ = variables;
}
public override void OnSolutionCallback()
{
{
Console.WriteLine(String.Format("Solution #{0}: time = {1:F2} s",
solution_count_, WallTime()));
foreach (IntVar v in variables_)
{
Console.WriteLine(
String.Format(" {0} = {1}", v.ShortString(), Value(v)));
}
solution_count_++;
}
}
public int SolutionCount()
{
return solution_count_;
}
private int solution_count_;
private IntVar[] variables_;
}
public class VarArraySolutionPrinterWithObjective : CpSolverSolutionCallback
{
public VarArraySolutionPrinterWithObjective(IntVar[] variables)
{
variables_ = variables;
}
public override void OnSolutionCallback()
{
{
Console.WriteLine(String.Format("Solution #{0}: time = {1:F2} s",
solution_count_, WallTime()));
Console.WriteLine(
String.Format(" objective value = {0}", ObjectiveValue()));
foreach (IntVar v in variables_)
{
Console.WriteLine(
String.Format(" {0} = {1}", v.ShortString(), Value(v)));
}
solution_count_++;
}
}
public int SolutionCount()
{
return solution_count_;
}
private int solution_count_;
private IntVar[] variables_;
}
public class CodeSamplesSat
{
static void CodeSample()
{
// Creates the model.
CpModel model = new CpModel();
// Creates the Boolean variable.
IntVar x = model.NewBoolVar("x");
}
static void LiteralSample()
{
CpModel model = new CpModel();
IntVar x = model.NewBoolVar("x");
ILiteral not_x = x.Not();
}
static void BoolOrSample()
{
CpModel model = new CpModel();
IntVar x = model.NewBoolVar("x");
IntVar y = model.NewBoolVar("y");
model.AddBoolOr(new ILiteral[] {x, y.Not()});
}
static void ReifiedSample()
{
CpModel model = new CpModel();
IntVar x = model.NewBoolVar("x");
IntVar y = model.NewBoolVar("y");
IntVar b = model.NewBoolVar("b");
// First version using a half-reified bool and.
model.AddBoolAnd(new ILiteral[] {x, y.Not()}).OnlyEnforceIf(b);
// Second version using implications.
model.AddImplication(b, x);
model.AddImplication(b, y.Not());
// Third version using bool or.
model.AddBoolOr(new ILiteral[] {b.Not(), x});
model.AddBoolOr(new ILiteral[] {b.Not(), y.Not()});
}
static void RabbitsAndPheasants()
{
// Creates the model.
CpModel model = new CpModel();
// Creates the variables.
IntVar r = model.NewIntVar(0, 100, "r");
IntVar p = model.NewIntVar(0, 100, "p");
// 20 heads.
model.Add(r + p == 20);
// 56 legs.
model.Add(4 * r + 2 * p == 56);
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
if (status == CpSolverStatus.Feasible)
{
Console.WriteLine(solver.Value(r) + " rabbits, and " +
solver.Value(p) + " pheasants");
}
}
static void BinpackingProblem()
{
// Data.
int bin_capacity = 100;
int slack_capacity = 20;
int num_bins = 10;
int[,] items = new int[,] { {20, 12}, {15, 12}, {30, 8}, {45, 5} };
int num_items = items.GetLength(0);
// Model.
CpModel model = new CpModel();
// Main variables.
IntVar[,] x = new IntVar[num_items, num_bins];
for (int i = 0; i < num_items; ++i)
{
int num_copies = items[i, 1];
for (int b = 0; b < num_bins; ++b)
{
x[i, b] = model.NewIntVar(0, num_copies, String.Format("x_{0}_{1}", i, b));
}
}
// Load variables.
IntVar[] load = new IntVar[num_bins];
for (int b = 0; b < num_bins; ++b)
{
load[b] = model.NewIntVar(0, bin_capacity, String.Format("load_{0}", b));
}
// Slack variables.
IntVar[] slacks = new IntVar[num_bins];
for (int b = 0; b < num_bins; ++b)
{
slacks[b] = model.NewBoolVar(String.Format("slack_{0}", b));
}
// Links load and x.
int[] sizes = new int[num_items];
for (int i = 0; i < num_items; ++i) {
sizes[i] = items[i, 0];
}
for (int b = 0; b < num_bins; ++b)
{
IntVar[] tmp = new IntVar[num_items];
for (int i = 0; i < num_items; ++i)
{
tmp[i] = x[i, b];
}
model.Add(load[b] == tmp.ScalProd(sizes));
}
// Place all items.
for (int i = 0; i < num_items; ++i)
{
IntVar[] tmp = new IntVar[num_bins];
for (int b = 0; b < num_bins; ++b)
{
tmp[b] = x[i, b];
}
model.Add(tmp.Sum() == items[i, 1]);
}
// Links load and slack.
int safe_capacity = bin_capacity - slack_capacity;
for (int b = 0; b < num_bins; ++b)
{
// slack[b] => load[b] <= safe_capacity.
model.Add(load[b] <= safe_capacity).OnlyEnforceIf(slacks[b]);
// not(slack[b]) => load[b] > safe_capacity.
model.Add(load[b] > safe_capacity).OnlyEnforceIf(slacks[b].Not());
}
// Maximize sum of slacks.
model.Maximize(slacks.Sum());
// Solves and prints out the solution.
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
Console.WriteLine(String.Format("Solve status: {0}", status));
if (status == CpSolverStatus.Optimal) {
Console.WriteLine(String.Format("Optimal objective value: {0}",
solver.ObjectiveValue));
for (int b = 0; b < num_bins; ++b)
{
Console.WriteLine(String.Format("load_{0} = {1}",
b, solver.Value(load[b])));
for (int i = 0; i < num_items; ++i)
{
Console.WriteLine(string.Format(" item_{0}_{1} = {2}",
i, b, solver.Value(x[i, b])));
}
}
}
Console.WriteLine("Statistics");
Console.WriteLine(
String.Format(" - conflicts : {0}", solver.NumConflicts()));
Console.WriteLine(
String.Format(" - branches : {0}", solver.NumBranches()));
Console.WriteLine(
String.Format(" - wall time : {0} s", solver.WallTime()));
}
static void IntervalSample()
{
CpModel model = new CpModel();
int horizon = 100;
IntVar start_var = model.NewIntVar(0, horizon, "start");
// C# code supports IntVar or integer constants in intervals.
int duration = 10;
IntVar end_var = model.NewIntVar(0, horizon, "end");
IntervalVar interval =
model.NewIntervalVar(start_var, duration, end_var, "interval");
}
static void OptionalIntervalSample()
{
CpModel model = new CpModel();
int horizon = 100;
IntVar start_var = model.NewIntVar(0, horizon, "start");
// C# code supports IntVar or integer constants in intervals.
int duration = 10;
IntVar end_var = model.NewIntVar(0, horizon, "end");
IntVar presence_var = model.NewBoolVar("presence");
IntervalVar interval = model.NewOptionalIntervalVar(
start_var, duration, end_var, presence_var, "interval");
}
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.Feasible)
{
Console.WriteLine("x = " + solver.Value(x));
Console.WriteLine("y = " + solver.Value(y));
Console.WriteLine("z = " + solver.Value(z));
}
}
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.Feasible)
{
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 MinimalCpSatAllSolutions()
{
// 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();
VarArraySolutionPrinter cb =
new VarArraySolutionPrinter(new IntVar[] {x, y, z});
solver.SearchAllSolutions(model, cb);
Console.WriteLine(String.Format("Number of solutions found: {0}",
cb.SolutionCount()));
}
static void Main()
{
Console.WriteLine("--- CodeSample ---");
CodeSample();
Console.WriteLine("--- LiteralSample ---");
LiteralSample();
Console.WriteLine("--- BoolOrSample ---");
BoolOrSample();
Console.WriteLine("--- ReifiedSample ---");
ReifiedSample();
Console.WriteLine("--- RabbitsAndPheasants ---");
RabbitsAndPheasants();
Console.WriteLine("--- BinpackingProblem ---");
BinpackingProblem();
Console.WriteLine("--- IntervalSample ---");
IntervalSample();
Console.WriteLine("--- OptionalIntervalSample ---");
OptionalIntervalSample();
Console.WriteLine("--- MinimalCpSat ---");
MinimalCpSat();
Console.WriteLine("--- MinimalCpSatWithTimeLimit ---");
MinimalCpSatWithTimeLimit();
Console.WriteLine("--- MinimalCpSatPrintIntermediateSolutions ---");
MinimalCpSatPrintIntermediateSolutions();
Console.WriteLine("--- MinimalCpSatAllSolutions ---");
MinimalCpSatAllSolutions();
}
}

5
ortools/sat/samples/binpacking_problem.cc
View File

@@ -15,7 +15,6 @@
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/cp_model_utils.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
namespace operations_research {
namespace sat {
@@ -24,10 +23,10 @@ void BinpackingProblem() {
// Data.
const int kBinCapacity = 100;
const int kSlackCapacity = 20;
const int kNumBins = 10;
const int kNumBins = 5;
const std::vector<std::vector<int>> items = {
{20, 12}, {15, 12}, {30, 8}, {45, 5}};
{20, 6}, {15, 6}, {30, 4}, {45, 3}};
const int num_items = items.size();
// Model.

128
ortools/sat/samples/binpacking_problem.cs Normal file
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@@ -0,0 +1,128 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class CodeSamplesSat
{
static void BinpackingProblem()
{
// Data.
int bin_capacity = 100;
int slack_capacity = 20;
int num_bins = 10;
int[,] items = new int[,] { {20, 12}, {15, 12}, {30, 8}, {45, 5} };
int num_items = items.GetLength(0);
// Model.
CpModel model = new CpModel();
// Main variables.
IntVar[,] x = new IntVar[num_items, num_bins];
for (int i = 0; i < num_items; ++i)
{
int num_copies = items[i, 1];
for (int b = 0; b < num_bins; ++b)
{
x[i, b] = model.NewIntVar(0, num_copies, String.Format("x_{0}_{1}", i, b));
}
}
// Load variables.
IntVar[] load = new IntVar[num_bins];
for (int b = 0; b < num_bins; ++b)
{
load[b] = model.NewIntVar(0, bin_capacity, String.Format("load_{0}", b));
}
// Slack variables.
IntVar[] slacks = new IntVar[num_bins];
for (int b = 0; b < num_bins; ++b)
{
slacks[b] = model.NewBoolVar(String.Format("slack_{0}", b));
}
// Links load and x.
int[] sizes = new int[num_items];
for (int i = 0; i < num_items; ++i) {
sizes[i] = items[i, 0];
}
for (int b = 0; b < num_bins; ++b)
{
IntVar[] tmp = new IntVar[num_items];
for (int i = 0; i < num_items; ++i)
{
tmp[i] = x[i, b];
}
model.Add(load[b] == tmp.ScalProd(sizes));
}
// Place all items.
for (int i = 0; i < num_items; ++i)
{
IntVar[] tmp = new IntVar[num_bins];
for (int b = 0; b < num_bins; ++b)
{
tmp[b] = x[i, b];
}
model.Add(tmp.Sum() == items[i, 1]);
}
// Links load and slack.
int safe_capacity = bin_capacity - slack_capacity;
for (int b = 0; b < num_bins; ++b)
{
// slack[b] => load[b] <= safe_capacity.
model.Add(load[b] <= safe_capacity).OnlyEnforceIf(slacks[b]);
// not(slack[b]) => load[b] > safe_capacity.
model.Add(load[b] > safe_capacity).OnlyEnforceIf(slacks[b].Not());
}
// Maximize sum of slacks.
model.Maximize(slacks.Sum());
Console.WriteLine(model.Model);
// Solves and prints out the solution.
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
Console.WriteLine(String.Format("Solve status: {0}", status));
if (status == CpSolverStatus.Optimal) {
Console.WriteLine(String.Format("Optimal objective value: {0}",
solver.ObjectiveValue));
for (int b = 0; b < num_bins; ++b)
{
Console.WriteLine(String.Format("load_{0} = {1}",
b, solver.Value(load[b])));
for (int i = 0; i < num_items; ++i)
{
Console.WriteLine(string.Format(" item_{0}_{1} = {2}",
i, b, solver.Value(x[i, b])));
}
}
}
Console.WriteLine("Statistics");
Console.WriteLine(String.Format(" - conflicts : {0}",
solver.NumConflicts()));
Console.WriteLine(String.Format(" - branches : {0}",
solver.NumBranches()));
Console.WriteLine(String.Format(" - wall time : {0} s",
}
static void Main()
{
BinpackingProblem();
}
}

4
ortools/sat/samples/binpacking_problem.py
View File

@@ -24,10 +24,10 @@ def BinpackingProblem():
# Data.
bin_capacity = 100
slack_capacity = 20
num_bins = 10
num_bins = 5
all_bins = range(num_bins)
items = [(20, 12), (15, 12), (30, 8), (45, 5)]
items = [(20, 6), (15, 6), (30, 4), (45, 3)]
num_items = len(items)
all_items = range(num_items)

1
ortools/sat/samples/bool_or_sample.cc
View File

@@ -15,7 +15,6 @@
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/cp_model_utils.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
namespace operations_research {
namespace sat {

30
ortools/sat/samples/bool_or_sample.cs Normal file
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@@ -0,0 +1,30 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class CodeSamplesSat
{
static void BoolOrSample()
{
CpModel model = new CpModel();
IntVar x = model.NewBoolVar("x");
IntVar y = model.newBoolVar("y");
model.AddBoolOr(new ILiteral[] {x, y.Not()});
}
static void Main() {
BoolOrSample();
}
}

1
ortools/sat/samples/code_sample.cc
View File

@@ -15,7 +15,6 @@
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/cp_model_utils.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
namespace operations_research {
namespace sat {

31
ortools/sat/samples/code_sample.cs Normal file
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@@ -0,0 +1,31 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class CodeSamplesSat
{
static void CodeSample()
{
// Creates the model.
CpModel model = new CpModel();
// Creates the Boolean variable.
IntVar x = model.NewBoolVar("x");
}
static void Main()
{
CodeSample();
}
}

5
ortools/sat/samples/interval_sample.cc
View File

@@ -15,7 +15,6 @@
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/cp_model_utils.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
namespace operations_research {
namespace sat {
@@ -33,9 +32,7 @@ void IntervalSample() {
return index;
};
auto new_constant = [&cp_model, &new_variable](int64 v) {
return new_variable(v, v);
};
auto new_constant = [&new_variable](int64 v) { return new_variable(v, v); };
auto new_interval = [&cp_model](int start, int duration, int end) {
const int index = cp_model.constraints_size();

35
ortools/sat/samples/interval_sample.cs Normal file
View File

@@ -0,0 +1,35 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class CodeSamplesSat
{
static void IntervalSample()
{
CpModel model = new CpModel();
int horizon = 100;
IntVar start_var = model.NewIntVar(0, horizon, "start");
// C# code supports IntVar or integer constants in intervals.
int duration = 10;
IntVar end_var = model.NewIntVar(0, horizon, "end");
IntervalVar interval =
model.NewIntervalVar(start_var, duration, end_var, "interval");
}
static void Main()
{
IntervalSample();
}
}

1
ortools/sat/samples/literal_sample.cc
View File

@@ -15,7 +15,6 @@
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/cp_model_utils.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
namespace operations_research {
namespace sat {

29
ortools/sat/samples/literal_sample.cs Normal file
View File

@@ -0,0 +1,29 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class CodeSamplesSat
{
static void LiteralSample()
{
CpModel model = new CpModel();
IntVar x = model.NewBoolVar("x");
ILiteral not_x = x.Not();
}
static void Main() {
LiteralSample();
}
}

5
ortools/sat/samples/optional_interval_sample.cc
View File

@@ -15,7 +15,6 @@
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/cp_model_utils.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
namespace operations_research {
namespace sat {
@@ -33,9 +32,7 @@ void OptionalIntervalSample() {
return index;
};
auto new_constant = [&cp_model, &new_variable](int64 v) {
return new_variable(v, v);
};
auto new_constant = [&new_variable](int64 v) { return new_variable(v, v); };
auto new_optional_interval = [&cp_model](int start, int duration, int end,
int presence) {

36
ortools/sat/samples/optional_interval_sample.cs Normal file
View File

@@ -0,0 +1,36 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class CodeSamplesSat
{
static void OptionalIntervalSample()
{
CpModel model = new CpModel();
int horizon = 100;
IntVar start_var = model.NewIntVar(0, horizon, "start");
// C# code supports IntVar or integer constants in intervals.
int duration = 10;
IntVar end_var = model.NewIntVar(0, horizon, "end");
IntVar presence_var = model.NewBoolVar("presence");
IntervalVar interval = model.NewOptionalIntervalVar(
start_var, duration, end_var, presence_var, "interval");
}
static void Main()
{
OptionalIntervalSample();
}
}

1
ortools/sat/samples/rabbits_and_pheasants.cc
View File

@@ -15,7 +15,6 @@
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/cp_model_utils.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
namespace operations_research {
namespace sat {

46
ortools/sat/samples/rabbits_and_pheasants.cs Normal file
View File

@@ -0,0 +1,46 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class CodeSamplesSat
{
static void RabbitsAndPheasants()
{
// Creates the model.
CpModel model = new CpModel();
// Creates the variables.
IntVar r = model.NewIntVar(0, 100, "r");
IntVar p = model.NewIntVar(0, 100, "p");
// 20 heads.
model.Add(r + p == 20);
// 56 legs.
model.Add(4 * r + 2 * p == 56);
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
CpSolverStatus status = solver.Solve(model);
if (status == CpSolverStatus.Feasible)
{
Console.WriteLine(solver.Value(r) + " rabbits, and " +
solver.Value(p) + " pheasants");
}
}
static void Main()
{
RabbitsAndPheasants();
}
}

1
ortools/sat/samples/reified_sample.cc
View File

@@ -15,7 +15,6 @@
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/cp_model_utils.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
namespace operations_research {
namespace sat {

42
ortools/sat/samples/reified_sample.cs Normal file
View File

@@ -0,0 +1,42 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class CodeSamplesSat
{
static void ReifiedSample()
{
CpModel model = new CpModel();
IntVar x = model.NewBoolVar("x");
IntVar y = model.NewBoolVar("y");
IntVar b = model.NewBoolVar("b");
// First version using a half-reified bool and.
model.AddBoolAnd(new ILiteral[] {x, y.Not()}).OnlyEnforceIf(b);
// Second version using implications.
model.AddImplication(b, x);
model.AddImplication(b, y.Not());
// Third version using bool or.
model.AddBoolOr(new ILiteral[] {b.Not(), x});
model.AddBoolOr(new ILiteral[] {b.Not(), y.Not()});
}
static void Main() {
ReifiedSample();
}
}

1
ortools/sat/samples/simple_solve.cc
View File

@@ -15,7 +15,6 @@
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/cp_model_utils.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
namespace operations_research {
namespace sat {

48
ortools/sat/samples/simple_solve.cs Normal file
View File

@@ -0,0 +1,48 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class CodeSamplesSat
{
static void SimpleSolve()
{
// 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.Feasible)
{
Console.WriteLine("x = " + solver.Value(x));
Console.WriteLine("y = " + solver.Value(y));
Console.WriteLine("z = " + solver.Value(z));
}
}
static void Main()
{
SimpleSolve();
}
}

77
ortools/sat/samples/solve_all_solutions.cs Normal file
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@@ -0,0 +1,77 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class VarArraySolutionPrinter : CpSolverSolutionCallback
{
public VarArraySolutionPrinter(IntVar[] variables)
{
variables_ = variables;
}
public override void OnSolutionCallback()
{
{
Console.WriteLine(String.Format("Solution #{0}: time = {1:F2} s",
solution_count_, WallTime()));
foreach (IntVar v in variables_)
{
Console.WriteLine(
String.Format(" {0} = {1}", v.ShortString(), Value(v)));
}
solution_count_++;
}
}
public int SolutionCount()
{
return solution_count_;
}
private int solution_count_;
private IntVar[] variables_;
}
public class CodeSamplesSat
{
static void MinimalCpSatAllSolutions()
{
// 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);
// Creates a solver and solves the model.
CpSolver solver = new CpSolver();
VarArraySolutionPrinter cb =
new VarArraySolutionPrinter(new IntVar[] {x, y, z});
solver.SearchAllSolutions(model, cb);
Console.WriteLine(String.Format("Number of solutions found: {0}",
cb.SolutionCount()));
}
static void Main()
{
MinimalCpSatAllSolutions();
}
}

1
ortools/sat/samples/solve_with_intermediate_solutions.cc
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@@ -15,7 +15,6 @@
#include "ortools/sat/cp_model_solver.h"
#include "ortools/sat/cp_model_utils.h"
#include "ortools/sat/model.h"
#include "ortools/sat/sat_parameters.pb.h"
namespace operations_research {
namespace sat {

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ortools/sat/samples/solve_with_intermediate_solutions.cs Normal file
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@@ -0,0 +1,81 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class VarArraySolutionPrinterWithObjective : CpSolverSolutionCallback
{
public VarArraySolutionPrinterWithObjective(IntVar[] variables)
{
variables_ = variables;
}
public override void OnSolutionCallback()
{
{
Console.WriteLine(String.Format("Solution #{0}: time = {1:F2} s",
solution_count_, WallTime()));
Console.WriteLine(
String.Format(" objective value = {0}", ObjectiveValue()));
foreach (IntVar v in variables_)
{
Console.WriteLine(
String.Format(" {0} = {1}", v.ShortString(), Value(v)));
}
solution_count_++;
}
}
public int SolutionCount()
{
return solution_count_;
}
private int solution_count_;
private IntVar[] variables_;
}
public class CodeSamplesSat
{
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.SearchAllSolutions(model, cb);
Console.WriteLine(String.Format('Number of solutions found: {0}',
cb.SolutionCount()));
}
static void Main()
{
MinimalCpSatPrintIntermediateSolutions();
}
}

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ortools/sat/samples/solve_with_time_limit.cs Normal file
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@@ -0,0 +1,52 @@
// Copyright 2010-2017 Google
// 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 Google.OrTools.Sat;
public class CodeSamplesSat
{
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");
// Adds a different constraint.
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.Feasible)
{
Console.WriteLine("x = " + solver.Value(x));
Console.WriteLine("y = " + solver.Value(y));
Console.WriteLine("z = " + solver.Value(z));
}
}
static void Main()
{
MinimalCpSatWithTimeLimit();
}
}