b027e57e95
- Currently not implemented... Add abseil patch - Add patches/absl-config.cmake Makefile: Add abseil-cpp on unix - Force abseil-cpp SHA1 to 45221cc note: Just before the PR #136 which break all CMake Makefile: Add abseil-cpp on windows - Force abseil-cpp SHA1 to 45221cc note: Just before the PR #136 which break all CMake CMake: Add abseil-cpp - Force abseil-cpp SHA1 to 45221cc note: Just before the PR #136 which break all CMake port to absl: C++ Part - Fix warning with the use of ABSL_MUST_USE_RESULT > The macro must appear as the very first part of a function declaration or definition: ... Note: past advice was to place the macro after the argument list. src: dependencies/sources/abseil-cpp-master/absl/base/attributes.h:418 - Rename enum after windows clash - Remove non compact table constraints - Change index type from int64 to int in routing library - Fix file_nonport compilation on windows - Fix another naming conflict with windows (NO_ERROR is a macro) - Cleanup hash containers; work on sat internals - Add optional_boolean sub-proto Sync cpp examples with internal code - reenable issue173 after reducing number of loops port to absl: Python Part - Add back cp_model.INT32_MIN|MAX for examples Update Python examples - Add random_tsp.py - Run words_square example - Run magic_square in python tests port to absl: Java Part - Fix compilation of the new routing parameters in java - Protect some code from SWIG parsing Update Java Examples port to absl: .Net Part Update .Net examples work on sat internals; Add C++ CP-SAT CpModelBuilder API; update sample code and recipes to use the new API; sync with internal code Remove VS 2015 in Appveyor-CI - abseil-cpp does not support VS 2015... improve tables upgrade C++ sat examples to use the new API; work on sat internals update license dates rewrite jobshop_ft06_distance.py to use the CP-SAT solver rename last example revert last commit more work on SAT internals fix
111 lines
4.3 KiB
C++
111 lines
4.3 KiB
C++
// Copyright 2010-2018 Google LLC
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// Linear programming example that shows how to use the API.
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#include "ortools/base/logging.h"
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#include "ortools/linear_solver/linear_solver.h"
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#include "ortools/linear_solver/linear_solver.pb.h"
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namespace operations_research {
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void RunLinearProgrammingExample(
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MPSolver::OptimizationProblemType optimization_problem_type) {
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MPSolver solver("LinearProgrammingExample", optimization_problem_type);
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const double infinity = solver.infinity();
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// x and y are continuous non-negative variables.
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MPVariable* const x = solver.MakeNumVar(0.0, infinity, "x");
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MPVariable* const y = solver.MakeNumVar(0.0, infinity, "y");
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// Objectif function: Maximize 3x + 4y).
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MPObjective* const objective = solver.MutableObjective();
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objective->SetCoefficient(x, 3);
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objective->SetCoefficient(y, 4);
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objective->SetMaximization();
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// x + 2y <= 14.
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MPConstraint* const c0 = solver.MakeRowConstraint(-infinity, 14.0);
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c0->SetCoefficient(x, 1);
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c0->SetCoefficient(y, 2);
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// 3x - y >= 0.
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MPConstraint* const c1 = solver.MakeRowConstraint(0.0, infinity);
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c1->SetCoefficient(x, 3);
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c1->SetCoefficient(y, -1);
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// x - y <= 2.
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MPConstraint* const c2 = solver.MakeRowConstraint(-infinity, 2.0);
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c2->SetCoefficient(x, 1);
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c2->SetCoefficient(y, -1);
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LOG(INFO) << "Number of variables = " << solver.NumVariables();
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LOG(INFO) << "Number of constraints = " << solver.NumConstraints();
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const MPSolver::ResultStatus result_status = solver.Solve();
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// Check that the problem has an optimal solution.
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if (result_status != MPSolver::OPTIMAL) {
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LOG(FATAL) << "The problem does not have an optimal solution!";
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}
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LOG(INFO) << "Solution:";
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LOG(INFO) << "x = " << x->solution_value();
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LOG(INFO) << "y = " << y->solution_value();
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LOG(INFO) << "Optimal objective value = " << objective->Value();
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LOG(INFO) << "";
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LOG(INFO) << "Advanced usage:";
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LOG(INFO) << "Problem solved in " << solver.wall_time() << " milliseconds";
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LOG(INFO) << "Problem solved in " << solver.iterations() << " iterations";
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LOG(INFO) << "x: reduced cost = " << x->reduced_cost();
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LOG(INFO) << "y: reduced cost = " << y->reduced_cost();
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const std::vector<double> activities = solver.ComputeConstraintActivities();
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LOG(INFO) << "c0: dual value = " << c0->dual_value()
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<< " activity = " << activities[c0->index()];
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LOG(INFO) << "c1: dual value = " << c1->dual_value()
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<< " activity = " << activities[c1->index()];
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LOG(INFO) << "c2: dual value = " << c2->dual_value()
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<< " activity = " << activities[c2->index()];
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}
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void RunAllExamples() {
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#if defined(USE_GLOP)
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LOG(INFO) << "---- Linear programming example with GLOP ----";
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RunLinearProgrammingExample(MPSolver::GLOP_LINEAR_PROGRAMMING);
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#endif // USE_GLOP
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#if defined(USE_CLP)
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LOG(INFO) << "---- Linear programming example with CLP ----";
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RunLinearProgrammingExample(MPSolver::CLP_LINEAR_PROGRAMMING);
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#endif // USE_CLP
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#if defined(USE_GLPK)
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LOG(INFO) << "---- Linear programming example with GLPK ----";
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RunLinearProgrammingExample(MPSolver::GLPK_LINEAR_PROGRAMMING);
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#endif // USE_GLPK
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#if defined(USE_SLM)
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LOG(INFO) << "---- Linear programming example with Sulum ----";
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RunLinearProgrammingExample(MPSolver::SULUM_LINEAR_PROGRAMMING);
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#endif // USE_SLM
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#if defined(USE_GUROBI)
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LOG(INFO) << "---- Linear programming example with Gurobi ----";
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RunLinearProgrammingExample(MPSolver::GUROBI_LINEAR_PROGRAMMING);
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#endif // USE_GUROBI
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#if defined(USE_CPLEX)
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LOG(INFO) << "---- Linear programming example with CPLEX ----";
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RunLinearProgrammingExample(MPSolver::CPLEX_LINEAR_PROGRAMMING);
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#endif // USE_CPLEX
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}
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} // namespace operations_research
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int main(int argc, char** argv) {
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google::InitGoogleLogging(argv[0]);
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FLAGS_logtostderr = 1;
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operations_research::RunAllExamples();
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return 0;
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}
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