Google OR-Tools v9.9
a fast and portable software suite for combinatorial optimization
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mip_tests.cc File Reference
#include "ortools/math_opt/solver_tests/mip_tests.h"
#include <cmath>
#include <initializer_list>
#include <limits>
#include <ostream>
#include <string>
#include <type_traits>
#include <utility>
#include "absl/log/check.h"
#include "absl/status/statusor.h"
#include "gtest/gtest.h"
#include "ortools/base/gmock.h"
#include "ortools/base/logging.h"
#include "ortools/math_opt/cpp/matchers.h"
#include "ortools/math_opt/cpp/math_opt.h"

Go to the source code of this file.

Namespaces

namespace  operations_research
 In SWIG mode, we don't want anything besides these top-level includes.
 
namespace  operations_research::math_opt
 An object oriented wrapper for quadratic constraints in ModelStorage.
 

Functions

std::ostream & operations_research::math_opt::operator<< (std::ostream &out, const SimpleMipTestParameters &params)
 
model operations_research::math_opt::Minimize (x)
 
 operations_research::math_opt::ASSERT_THAT (solver->Update(), IsOkAndHolds(DidUpdate()))
 
 operations_research::math_opt::ASSERT_THAT (solver->SolveWithoutUpdate(), IsOkAndHolds(IsOptimal(0.5)))
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, MakeIntegralWithNonIntegralBounds)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, MakeInteger)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, ObjDir)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, ObjOffset)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, LinearObjCoef)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, VariableLb)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, VariableUb)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, LinearConstraintLb)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, LinearConstraintUb)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, LinearConstraintCoefficient)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, AddVariable)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, AddLinearConstraint)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, DeleteVariable)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, DeleteLinearConstraint)
 
 operations_research::math_opt::TEST_P (IncrementalMipTest, ChangeBoundsWithTemporaryInversion)
 

Variables

<=x<=1 IncrementalMipTest::IncrementalMipTest() :model_("incremental_solve_test"), x_(model_.AddContinuousVariable(0.0, 1.0, "x")), y_(model_.AddIntegerVariable(0.0, 2.0, "y")), c_(model_.AddLinearConstraint(0<=x_+y_<=1.5, "c")) { model_.Maximize(3.0 *x_+2.0 *y_+0.1);solver_=IncrementalSolver::New(&model_, TestedSolver()).value();const SolveResult first_solve=solver_->Solve().value();CHECK(first_solve.has_primal_feasible_solution());CHECK_LE(std::abs(first_solve.objective_value() - 3.6), kTolerance)<< first_solve.objective_value();} namespace { TEST_P(SimpleMipTest, OneVarMax) { Model model;const Variable x=model.AddVariable(0.0, 4.0, false, "x");model.Maximize(2.0 *x);ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));ASSERT_THAT(result, IsOptimal(8.0));EXPECT_THAT(result.variable_values(), IsNear({{x, 4.0}}));} TEST_P(SimpleMipTest, OneVarMin) { Model model;const Variable x=model.AddVariable(-2.4, 4.0, false, "x");model.Minimize(2.0 *x);ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));ASSERT_THAT(result, IsOptimal(-4.8));EXPECT_THAT(result.variable_values(), IsNear({{x, -2.4}}));} TEST_P(SimpleMipTest, OneIntegerVar) { Model model;const Variable x=model.AddVariable(0.0, 4.5, true, "x");model.Maximize(2.0 *x);ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));ASSERT_THAT(result, IsOptimal(8.0));EXPECT_THAT(result.variable_values(), IsNear({{x, 4.0}}));} TEST_P(SimpleMipTest, SimpleLinearConstraint) { Model model;const Variable x=model.AddBinaryVariable("x");const Variable y=model.AddBinaryVariable("y");model.Maximize(2.0 *x+y);model.AddLinearConstraint(0.0<=x+y<=1.5, "c");ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));ASSERT_THAT(result, IsOptimal(2.0));EXPECT_THAT(result.variable_values(), IsNear({{x, 1}, {y, 0}}));} TEST_P(SimpleMipTest, Unbounded) { Model model;const Variable x=model.AddVariable(0.0, kInf, true, "x");model.Maximize(2.0 *x);ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));if(GetParam().report_unboundness_correctly) { ASSERT_THAT(result, TerminatesWithOneOf({TerminationReason::kUnbounded, TerminationReason::kInfeasibleOrUnbounded}));} else { ASSERT_THAT(result, TerminatesWith(TerminationReason::kOtherError));} } TEST_P(SimpleMipTest, Infeasible) { Model model;const Variable x=model.AddVariable(0.0, 3.0, true, "x");model.Maximize(2.0 *x);model.AddLinearConstraint(x >=4.0);ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));ASSERT_THAT(result, TerminatesWith(TerminationReason::kInfeasible));} TEST_P(SimpleMipTest, FractionalBoundsContainNoInteger) { if(GetParam().solver_type==SolverType::kGurobi) { GTEST_SKIP()<< "TODO(b/272298816): Gurobi bindings are broken here.";} Model model;const Variable x=model.AddIntegerVariable(0.5, 0.6, "x");model.Maximize(x);EXPECT_THAT(Solve(model, GetParam().solver_type), IsOkAndHolds(TerminatesWith(TerminationReason::kInfeasible)));} TEST_P(IncrementalMipTest, EmptyUpdate) { ASSERT_THAT(solver_->Update(), IsOkAndHolds(DidUpdate()));ASSERT_OK_AND_ASSIGN(const SolveResult result, solver_->SolveWithoutUpdate());ASSERT_THAT(result, IsOptimal(3.6));EXPECT_THAT(result.variable_values(), IsNear({{x_, 0.5}, {y_, 1.0}}));} TEST_P(IncrementalMipTest, MakeContinuous) { model_.set_continuous(y_);ASSERT_THAT(solver_->Update(), IsOkAndHolds(DidUpdate()));ASSERT_OK_AND_ASSIGN(const SolveResult result, solver_->SolveWithoutUpdate());ASSERT_THAT(result, IsOptimal(4.1));EXPECT_THAT(result.variable_values(), IsNear({{x_, 1.0}, {y_, 0.5}}));} TEST_P(IncrementalMipTest, DISABLED_MakeContinuousWithNonIntegralBounds) { solver_.reset();Model model("bounds");const Variable x=model.AddIntegerVariable(0.5, 1.5, "x");model.Maximize(x);ASSERT_OK_AND_ASSIGN(const auto solver, IncrementalSolver::New(&model, TestedSolver()));ASSERT_THAT(solver->Solve(), IsOkAndHolds(IsOptimal(1.0)));model.set_continuous(x);ASSERT_THAT(solver->Update(), IsOkAndHolds(DidUpdate()));ASSERT_THAT(solver- operations_research::math_opt::SolveWithoutUpdate )()
 
<=x<=1 IncrementalMipTest::IncrementalMipTest() :model_("incremental_solve_test"), x_(model_.AddContinuousVariable(0.0, 1.0, "x")), y_(model_.AddIntegerVariable(0.0, 2.0, "y")), c_(model_.AddLinearConstraint(0<=x_+y_<=1.5, "c")) { model_.Maximize(3.0 *x_+2.0 *y_+0.1);solver_=IncrementalSolver::New(&model_, TestedSolver()).value();const SolveResult first_solve=solver_->Solve().value();CHECK(first_solve.has_primal_feasible_solution());CHECK_LE(std::abs(first_solve.objective_value() - 3.6), kTolerance)<< first_solve.objective_value();} namespace { TEST_P(SimpleMipTest, OneVarMax) { Model model;const Variable x=model.AddVariable(0.0, 4.0, false, "x");model.Maximize(2.0 *x);ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));ASSERT_THAT(result, IsOptimal(8.0));EXPECT_THAT(result.variable_values(), IsNear({{x, 4.0}}));} TEST_P(SimpleMipTest, OneVarMin) { Model model;const Variable x=model.AddVariable(-2.4, 4.0, false, "x");model.Minimize(2.0 *x);ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));ASSERT_THAT(result, IsOptimal(-4.8));EXPECT_THAT(result.variable_values(), IsNear({{x, -2.4}}));} TEST_P(SimpleMipTest, OneIntegerVar) { Model model;const Variable x=model.AddVariable(0.0, 4.5, true, "x");model.Maximize(2.0 *x);ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));ASSERT_THAT(result, IsOptimal(8.0));EXPECT_THAT(result.variable_values(), IsNear({{x, 4.0}}));} TEST_P(SimpleMipTest, SimpleLinearConstraint) { Model model;const Variable x=model.AddBinaryVariable("x");const Variable y=model.AddBinaryVariable("y");model.Maximize(2.0 *x+y);model.AddLinearConstraint(0.0<=x+y<=1.5, "c");ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));ASSERT_THAT(result, IsOptimal(2.0));EXPECT_THAT(result.variable_values(), IsNear({{x, 1}, {y, 0}}));} TEST_P(SimpleMipTest, Unbounded) { Model model;const Variable x=model.AddVariable(0.0, kInf, true, "x");model.Maximize(2.0 *x);ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));if(GetParam().report_unboundness_correctly) { ASSERT_THAT(result, TerminatesWithOneOf({TerminationReason::kUnbounded, TerminationReason::kInfeasibleOrUnbounded}));} else { ASSERT_THAT(result, TerminatesWith(TerminationReason::kOtherError));} } TEST_P(SimpleMipTest, Infeasible) { Model model;const Variable x=model.AddVariable(0.0, 3.0, true, "x");model.Maximize(2.0 *x);model.AddLinearConstraint(x >=4.0);ASSERT_OK_AND_ASSIGN(const SolveResult result, Solve(model, GetParam().solver_type));ASSERT_THAT(result, TerminatesWith(TerminationReason::kInfeasible));} TEST_P(SimpleMipTest, FractionalBoundsContainNoInteger) { if(GetParam().solver_type==SolverType::kGurobi) { GTEST_SKIP()<< "TODO(b/272298816): Gurobi bindings are broken here.";} Model model;const Variable x=model.AddIntegerVariable(0.5, 0.6, "x");model.Maximize(x);EXPECT_THAT(Solve(model, GetParam().solver_type), IsOkAndHolds(TerminatesWith(TerminationReason::kInfeasible)));} TEST_P(IncrementalMipTest, EmptyUpdate) { ASSERT_THAT(solver_->Update(), IsOkAndHolds(DidUpdate()));ASSERT_OK_AND_ASSIGN(const SolveResult result, solver_->SolveWithoutUpdate());ASSERT_THAT(result, IsOptimal(3.6));EXPECT_THAT(result.variable_values(), IsNear({{x_, 0.5}, {y_, 1.0}}));} TEST_P(IncrementalMipTest, MakeContinuous) { model_.set_continuous(y_);ASSERT_THAT(solver_->Update(), IsOkAndHolds(DidUpdate()));ASSERT_OK_AND_ASSIGN(const SolveResult result, solver_->SolveWithoutUpdate());ASSERT_THAT(result, IsOptimal(4.1));EXPECT_THAT(result.variable_values(), IsNear({{x_, 1.0}, {y_, 0.5}}));} TEST_P(IncrementalMipTest, DISABLED_MakeContinuousWithNonIntegralBounds) { solver_.reset();Model model("bounds");const Variable x=model.AddIntegerVariable(0.5, 1.5, "x");model.Maximize(x);ASSERT_OK_AND_ASSIGN(const auto solver, IncrementalSolver::New(&model, TestedSolver()));ASSERT_THAT(solver->Solve(), IsOkAndHolds(IsOptimal(1.0)));model.set_continuous(x);ASSERT_THAT(solver->Update(), IsOkAndHolds(DidUpdate()));ASSERT_THAT(solver- operations_research::math_opt::IsOkAndHolds )(IsOptimal(1.5)))