// 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 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::MODEL_SAT) { // 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::MODEL_SAT) { // Get the value of x in the solution. const int64 value_x = response.solution(x); LOG(INFO) << "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& vars, const std::vector& 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); // Solving part. 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(int argc, char** argv) { operations_research::sat::SimpleSolve(); operations_research::sat::SolveWithTimeLimit(); operations_research::sat::MinimalSatPrintIntermediateSolutions(); operations_research::sat::MinimalSatSearchForAllSolutions(); return EXIT_SUCCESS; }