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linear_solver.cc
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linear_solver.cc
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// Copyright 2010-2024 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.
#include "ortools/linear_solver/linear_solver.h"
#if !defined(_MSC_VER)
#include <unistd.h>
#endif
#include <algorithm>
#include <atomic>
#include <cmath>
#include <cstddef>
#include <cstdint>
#include <functional>
#include <iostream>
#include <limits>
#include <optional>
#include <string>
#include <utility>
#include <vector>
#include "absl/base/const_init.h"
#include "absl/container/flat_hash_map.h"
#include "absl/container/flat_hash_set.h"
#include "absl/flags/flag.h"
#include "absl/log/check.h"
#include "absl/status/status.h"
#include "absl/status/statusor.h"
#include "absl/strings/ascii.h"
#include "absl/strings/match.h"
#include "absl/strings/str_cat.h"
#include "absl/strings/str_format.h"
#include "absl/strings/str_replace.h"
#include "absl/strings/string_view.h"
#include "absl/synchronization/mutex.h"
#include "absl/synchronization/notification.h"
#include "absl/time/clock.h"
#include "absl/time/time.h"
#include "google/protobuf/text_format.h"
#include "ortools/base/accurate_sum.h"
#include "ortools/base/logging.h"
#include "ortools/base/map_util.h"
#include "ortools/base/stl_util.h"
#include "ortools/base/threadpool.h"
#include "ortools/linear_solver/linear_expr.h"
#include "ortools/linear_solver/linear_solver.pb.h"
#include "ortools/linear_solver/linear_solver_callback.h"
#include "ortools/linear_solver/model_exporter.h"
#include "ortools/linear_solver/model_validator.h"
#include "ortools/port/file.h"
#include "ortools/port/proto_utils.h"
#include "ortools/util/fp_utils.h"
#include "ortools/util/lazy_mutable_copy.h"
#include "ortools/util/time_limit.h"
ABSL_FLAG(bool, verify_solution, false,
"Systematically verify the solution when calling Solve()"
", and change the return value of Solve() to ABNORMAL if"
" an error was detected.");
ABSL_FLAG(bool, log_verification_errors, true,
"If --verify_solution is set: LOG(ERROR) all errors detected"
" during the verification of the solution.");
ABSL_FLAG(bool, linear_solver_enable_verbose_output, false,
"If set, enables verbose output for the solver. Setting this flag"
" is the same as calling MPSolver::EnableOutput().");
ABSL_FLAG(bool, mpsolver_bypass_model_validation, false,
"If set, the user-provided Model won't be verified before Solve()."
" Invalid models will typically trigger various error responses"
" from the underlying solvers; sometimes crashes.");
namespace operations_research {
bool SolverTypeIsMip(MPModelRequest::SolverType solver_type) {
switch (solver_type) {
case MPModelRequest::PDLP_LINEAR_PROGRAMMING:
case MPModelRequest::GLOP_LINEAR_PROGRAMMING:
case MPModelRequest::CLP_LINEAR_PROGRAMMING:
case MPModelRequest::GLPK_LINEAR_PROGRAMMING:
case MPModelRequest::GUROBI_LINEAR_PROGRAMMING:
case MPModelRequest::HIGHS_LINEAR_PROGRAMMING:
case MPModelRequest::XPRESS_LINEAR_PROGRAMMING:
case MPModelRequest::CPLEX_LINEAR_PROGRAMMING:
return false;
case MPModelRequest::SCIP_MIXED_INTEGER_PROGRAMMING:
case MPModelRequest::GLPK_MIXED_INTEGER_PROGRAMMING:
case MPModelRequest::CBC_MIXED_INTEGER_PROGRAMMING:
case MPModelRequest::GUROBI_MIXED_INTEGER_PROGRAMMING:
case MPModelRequest::KNAPSACK_MIXED_INTEGER_PROGRAMMING:
case MPModelRequest::BOP_INTEGER_PROGRAMMING:
case MPModelRequest::SAT_INTEGER_PROGRAMMING:
case MPModelRequest::HIGHS_MIXED_INTEGER_PROGRAMMING:
case MPModelRequest::XPRESS_MIXED_INTEGER_PROGRAMMING:
case MPModelRequest::CPLEX_MIXED_INTEGER_PROGRAMMING:
return true;
}
LOG(DFATAL) << "Invalid SolverType: " << solver_type;
return false;
}
double MPConstraint::GetCoefficient(const MPVariable* const var) const {
DLOG_IF(DFATAL, !interface_->solver_->OwnsVariable(var)) << var;
if (var == nullptr) return 0.0;
return gtl::FindWithDefault(coefficients_, var);
}
void MPConstraint::SetCoefficient(const MPVariable* const var, double coeff) {
DLOG_IF(DFATAL, !interface_->solver_->OwnsVariable(var)) << var;
if (var == nullptr) return;
if (coeff == 0.0) {
auto it = coefficients_.find(var);
// If setting a coefficient to 0 when this coefficient did not
// exist or was already 0, do nothing: skip
// interface_->SetCoefficient() and do not store a coefficient in
// the map. Note that if the coefficient being set to 0 did exist
// and was not 0, we do have to keep a 0 in the coefficients_ map,
// because the extraction of the constraint might rely on it,
// depending on the underlying solver.
if (it != coefficients_.end() && it->second != 0.0) {
const double old_value = it->second;
it->second = 0.0;
interface_->SetCoefficient(this, var, 0.0, old_value);
}
return;
}
auto insertion_result = coefficients_.insert(std::make_pair(var, coeff));
const double old_value =
insertion_result.second ? 0.0 : insertion_result.first->second;
insertion_result.first->second = coeff;
interface_->SetCoefficient(this, var, coeff, old_value);
}
void MPConstraint::Clear() {
interface_->ClearConstraint(this);
coefficients_.clear();
}
void MPConstraint::SetBounds(double lb, double ub) {
const bool change = lb != lb_ || ub != ub_;
lb_ = lb;
ub_ = ub;
if (change && interface_->constraint_is_extracted(index_)) {
interface_->SetConstraintBounds(index_, lb_, ub_);
}
}
double MPConstraint::dual_value() const {
if (!interface_->IsContinuous()) {
LOG(DFATAL) << "Dual value only available for continuous problems";
return 0.0;
}
if (!interface_->CheckSolutionIsSynchronizedAndExists()) return 0.0;
return dual_value_;
}
MPSolver::BasisStatus MPConstraint::basis_status() const {
if (!interface_->IsContinuous()) {
LOG(DFATAL) << "Basis status only available for continuous problems";
return MPSolver::FREE;
}
if (!interface_->CheckSolutionIsSynchronizedAndExists()) {
return MPSolver::FREE;
}
// This is done lazily as this method is expected to be rarely used.
return interface_->row_status(index_);
}
bool MPConstraint::ContainsNewVariables() {
const int last_variable_index = interface_->last_variable_index();
for (const auto& entry : coefficients_) {
const int variable_index = entry.first->index();
if (variable_index >= last_variable_index ||
!interface_->variable_is_extracted(variable_index)) {
return true;
}
}
return false;
}
// ----- MPObjective -----
double MPObjective::GetCoefficient(const MPVariable* const var) const {
DLOG_IF(DFATAL, !interface_->solver_->OwnsVariable(var)) << var;
if (var == nullptr) return 0.0;
return gtl::FindWithDefault(coefficients_, var);
}
void MPObjective::SetCoefficient(const MPVariable* const var, double coeff) {
DLOG_IF(DFATAL, !interface_->solver_->OwnsVariable(var)) << var;
if (var == nullptr) return;
if (coeff == 0.0) {
auto it = coefficients_.find(var);
// See the discussion on MPConstraint::SetCoefficient() for 0 coefficients,
// the same reasoning applies here.
if (it == coefficients_.end() || it->second == 0.0) return;
it->second = 0.0;
} else {
coefficients_[var] = coeff;
}
interface_->SetObjectiveCoefficient(var, coeff);
}
void MPObjective::SetOffset(double value) {
offset_ = value;
interface_->SetObjectiveOffset(offset_);
}
namespace {
void CheckLinearExpr(const MPSolver& solver, const LinearExpr& linear_expr) {
for (auto var_value_pair : linear_expr.terms()) {
CHECK(solver.OwnsVariable(var_value_pair.first))
<< "Bad MPVariable* in LinearExpr, did you try adding an integer to an "
"MPVariable* directly?";
}
}
} // namespace
void MPObjective::OptimizeLinearExpr(const LinearExpr& linear_expr,
bool is_maximization) {
CheckLinearExpr(*interface_->solver_, linear_expr);
interface_->ClearObjective();
coefficients_.clear();
SetOffset(linear_expr.offset());
for (const auto& kv : linear_expr.terms()) {
SetCoefficient(kv.first, kv.second);
}
SetOptimizationDirection(is_maximization);
}
void MPObjective::AddLinearExpr(const LinearExpr& linear_expr) {
CheckLinearExpr(*interface_->solver_, linear_expr);
SetOffset(offset_ + linear_expr.offset());
for (const auto& kv : linear_expr.terms()) {
SetCoefficient(kv.first, GetCoefficient(kv.first) + kv.second);
}
}
void MPObjective::Clear() {
interface_->ClearObjective();
coefficients_.clear();
offset_ = 0.0;
SetMinimization();
}
void MPObjective::SetOptimizationDirection(bool maximize) {
// Note(user): The maximize_ bool would more naturally belong to the
// MPObjective, but it actually has to be a member of MPSolverInterface,
// because some implementations (such as GLPK) need that bool for the
// MPSolverInterface constructor, i.e. at a time when the MPObjective is not
// constructed yet (MPSolverInterface is always built before MPObjective
// when a new MPSolver is constructed).
interface_->maximize_ = maximize;
interface_->SetOptimizationDirection(maximize);
}
bool MPObjective::maximization() const { return interface_->maximize_; }
bool MPObjective::minimization() const { return !interface_->maximize_; }
double MPObjective::Value() const {
// Note(user): implementation-wise, the objective value belongs more
// naturally to the MPSolverInterface, since all of its implementations write
// to it directly.
return interface_->objective_value();
}
double MPObjective::BestBound() const {
// Note(user): the best objective bound belongs to the interface for the
// same reasons as the objective value does.
return interface_->best_objective_bound();
}
// ----- MPVariable -----
double MPVariable::solution_value() const {
if (!interface_->CheckSolutionIsSynchronizedAndExists()) return 0.0;
// If the underlying solver supports integer variables, and this is an integer
// variable, we round the solution value (i.e., clients usually expect precise
// integer values for integer variables).
return (integer_ && interface_->IsMIP()) ? round(solution_value_)
: solution_value_;
}
double MPVariable::unrounded_solution_value() const {
if (!interface_->CheckSolutionIsSynchronizedAndExists()) return 0.0;
return solution_value_;
}
double MPVariable::reduced_cost() const {
if (!interface_->IsContinuous()) {
LOG(DFATAL) << "Reduced cost only available for continuous problems";
return 0.0;
}
if (!interface_->CheckSolutionIsSynchronizedAndExists()) return 0.0;
return reduced_cost_;
}
MPSolver::BasisStatus MPVariable::basis_status() const {
if (!interface_->IsContinuous()) {
LOG(DFATAL) << "Basis status only available for continuous problems";
return MPSolver::FREE;
}
if (!interface_->CheckSolutionIsSynchronizedAndExists()) {
return MPSolver::FREE;
}
// This is done lazily as this method is expected to be rarely used.
return interface_->column_status(index_);
}
void MPVariable::SetBounds(double lb, double ub) {
const bool change = lb != lb_ || ub != ub_;
lb_ = lb;
ub_ = ub;
if (change && interface_->variable_is_extracted(index_)) {
interface_->SetVariableBounds(index_, lb_, ub_);
}
}
void MPVariable::SetInteger(bool integer) {
if (integer_ != integer) {
integer_ = integer;
if (interface_->variable_is_extracted(index_)) {
interface_->SetVariableInteger(index_, integer);
}
}
}
void MPVariable::SetBranchingPriority(int priority) {
if (priority == branching_priority_) return;
branching_priority_ = priority;
interface_->BranchingPriorityChangedForVariable(index_);
}
// ----- Interface shortcuts -----
bool MPSolver::IsMIP() const { return interface_->IsMIP(); }
std::string MPSolver::SolverVersion() const {
return interface_->SolverVersion();
}
void* MPSolver::underlying_solver() { return interface_->underlying_solver(); }
// ---- Solver-specific parameters ----
absl::Status MPSolver::SetNumThreads(int num_threads) {
if (num_threads < 1) {
return absl::InvalidArgumentError("num_threads must be a positive number.");
}
const absl::Status status = interface_->SetNumThreads(num_threads);
if (status.ok()) {
num_threads_ = num_threads;
}
return status;
}
bool MPSolver::SetSolverSpecificParametersAsString(
const std::string& parameters) {
solver_specific_parameter_string_ = parameters;
return interface_->SetSolverSpecificParametersAsString(parameters);
}
// ----- Solver -----
#if defined(USE_BOP)
extern MPSolverInterface* BuildBopInterface(MPSolver* const solver);
#endif
#if defined(USE_CBC)
extern MPSolverInterface* BuildCBCInterface(MPSolver* const solver);
#endif
#if defined(USE_CLP) || defined(USE_CBC)
extern MPSolverInterface* BuildCLPInterface(MPSolver* const solver);
#endif
#if defined(USE_GLOP)
extern MPSolverInterface* BuildGLOPInterface(MPSolver* const solver);
#endif
#if defined(USE_GLPK)
extern MPSolverInterface* BuildGLPKInterface(bool mip, MPSolver* const solver);
#endif
#if defined(USE_HIGHS)
extern MPSolverInterface* BuildHighsInterface(bool mip, MPSolver* const solver);
#endif
#if defined(USE_PDLP)
extern MPSolverInterface* BuildPdlpInterface(MPSolver* const solver);
#endif
extern MPSolverInterface* BuildSatInterface(MPSolver* const solver);
#if defined(USE_SCIP)
extern MPSolverInterface* BuildSCIPInterface(MPSolver* const solver);
#endif
extern MPSolverInterface* BuildGurobiInterface(bool mip,
MPSolver* const solver);
#if defined(USE_CPLEX)
extern MPSolverInterface* BuildCplexInterface(bool mip, MPSolver* const solver);
#endif
extern MPSolverInterface* BuildXpressInterface(bool mip,
MPSolver* const solver);
namespace {
MPSolverInterface* BuildSolverInterface(MPSolver* const solver) {
DCHECK(solver != nullptr);
switch (solver->ProblemType()) {
#if defined(USE_BOP)
case MPSolver::BOP_INTEGER_PROGRAMMING:
return BuildBopInterface(solver);
#endif
#if defined(USE_CBC)
case MPSolver::CBC_MIXED_INTEGER_PROGRAMMING:
return BuildCBCInterface(solver);
#endif
#if defined(USE_CLP) || defined(USE_CBC)
case MPSolver::CLP_LINEAR_PROGRAMMING:
return BuildCLPInterface(solver);
#endif
#if defined(USE_GLOP)
case MPSolver::GLOP_LINEAR_PROGRAMMING:
return BuildGLOPInterface(solver);
#endif
#if defined(USE_GLPK)
case MPSolver::GLPK_LINEAR_PROGRAMMING:
return BuildGLPKInterface(false, solver);
case MPSolver::GLPK_MIXED_INTEGER_PROGRAMMING:
return BuildGLPKInterface(true, solver);
#endif
#if defined(USE_HIGHS)
case MPSolver::HIGHS_LINEAR_PROGRAMMING:
return BuildHighsInterface(false, solver);
case MPSolver::HIGHS_MIXED_INTEGER_PROGRAMMING:
return BuildHighsInterface(true, solver);
#endif
#if defined(USE_PDLP)
case MPSolver::PDLP_LINEAR_PROGRAMMING:
return BuildPdlpInterface(solver);
#endif
case MPSolver::SAT_INTEGER_PROGRAMMING:
return BuildSatInterface(solver);
#if defined(USE_SCIP)
case MPSolver::SCIP_MIXED_INTEGER_PROGRAMMING:
return BuildSCIPInterface(solver);
#endif
case MPSolver::GUROBI_LINEAR_PROGRAMMING:
return BuildGurobiInterface(false, solver);
case MPSolver::GUROBI_MIXED_INTEGER_PROGRAMMING:
return BuildGurobiInterface(true, solver);
#if defined(USE_CPLEX)
case MPSolver::CPLEX_LINEAR_PROGRAMMING:
return BuildCplexInterface(false, solver);
case MPSolver::CPLEX_MIXED_INTEGER_PROGRAMMING:
return BuildCplexInterface(true, solver);
#endif
case MPSolver::XPRESS_MIXED_INTEGER_PROGRAMMING:
return BuildXpressInterface(true, solver);
case MPSolver::XPRESS_LINEAR_PROGRAMMING:
return BuildXpressInterface(false, solver);
default:
// TODO(user): Revert to the best *available* interface.
LOG(FATAL) << "Linear solver not recognized.";
}
return nullptr;
}
} // namespace
namespace {
int NumDigits(int n) {
// Number of digits needed to write a non-negative integer in base 10.
// Note(user): max(1, log(0) + 1) == max(1, -inf) == 1.
#if defined(_MSC_VER)
return static_cast<int>(std::max(1.0L, log(1.0L * n) / log(10.0L) + 1.0));
#else
return static_cast<int>(std::max(1.0, log10(static_cast<double>(n)) + 1.0));
#endif
}
} // namespace
MPSolver::MPSolver(const std::string& name,
OptimizationProblemType problem_type)
: name_(name),
problem_type_(problem_type),
construction_time_(absl::Now()) {
interface_.reset(BuildSolverInterface(this));
if (absl::GetFlag(FLAGS_linear_solver_enable_verbose_output)) {
EnableOutput();
}
objective_.reset(new MPObjective(interface_.get()));
}
MPSolver::~MPSolver() { Clear(); }
extern bool GurobiIsCorrectlyInstalled();
extern bool XpressIsCorrectlyInstalled();
// static
bool MPSolver::SupportsProblemType(OptimizationProblemType problem_type) {
#ifdef USE_BOP
if (problem_type == BOP_INTEGER_PROGRAMMING) return true;
#endif
#ifdef USE_CBC
if (problem_type == CBC_MIXED_INTEGER_PROGRAMMING) return true;
#endif
#ifdef USE_CLP
if (problem_type == CLP_LINEAR_PROGRAMMING) return true;
#endif
#ifdef USE_GLOP
if (problem_type == GLOP_LINEAR_PROGRAMMING) return true;
#endif
#ifdef USE_GLPK
if (problem_type == GLPK_LINEAR_PROGRAMMING ||
problem_type == GLPK_MIXED_INTEGER_PROGRAMMING) {
return true;
}
#endif
#ifdef USE_HIGHS
if (problem_type == HIGHS_MIXED_INTEGER_PROGRAMMING ||
problem_type == HIGHS_LINEAR_PROGRAMMING) {
return true;
}
#endif
#ifdef USE_PDLP
if (problem_type == PDLP_LINEAR_PROGRAMMING) return true;
#endif
if (problem_type == GUROBI_LINEAR_PROGRAMMING ||
problem_type == GUROBI_MIXED_INTEGER_PROGRAMMING) {
return GurobiIsCorrectlyInstalled();
}
if (problem_type == SAT_INTEGER_PROGRAMMING) return true;
#ifdef USE_SCIP
if (problem_type == SCIP_MIXED_INTEGER_PROGRAMMING) return true;
#endif
#ifdef USE_CPLEX
if (problem_type == CPLEX_LINEAR_PROGRAMMING ||
problem_type == CPLEX_MIXED_INTEGER_PROGRAMMING) {
return true;
}
#endif
if (problem_type == XPRESS_MIXED_INTEGER_PROGRAMMING ||
problem_type == XPRESS_LINEAR_PROGRAMMING) {
return XpressIsCorrectlyInstalled();
}
return false;
}
// TODO(user): post c++ 14, instead use
// std::pair<MPSolver::OptimizationProblemType, const absl::string_view>
// once pair gets a constexpr constructor.
namespace {
struct NamedOptimizationProblemType {
MPSolver::OptimizationProblemType problem_type;
absl::string_view name;
};
} // namespace
#if defined(_MSC_VER)
const
#else
constexpr
#endif
NamedOptimizationProblemType kOptimizationProblemTypeNames[] = {
{MPSolver::GLOP_LINEAR_PROGRAMMING, "glop"},
{MPSolver::CLP_LINEAR_PROGRAMMING, "clp"},
{MPSolver::GUROBI_LINEAR_PROGRAMMING, "gurobi_lp"},
{MPSolver::GLPK_LINEAR_PROGRAMMING, "glpk_lp"},
{MPSolver::HIGHS_LINEAR_PROGRAMMING, "highs_lp"},
{MPSolver::CPLEX_LINEAR_PROGRAMMING, "cplex_lp"},
{MPSolver::XPRESS_LINEAR_PROGRAMMING, "xpress_lp"},
{MPSolver::SCIP_MIXED_INTEGER_PROGRAMMING, "scip"},
{MPSolver::CBC_MIXED_INTEGER_PROGRAMMING, "cbc"},
{MPSolver::SAT_INTEGER_PROGRAMMING, "sat"},
{MPSolver::BOP_INTEGER_PROGRAMMING, "bop"},
{MPSolver::GUROBI_MIXED_INTEGER_PROGRAMMING, "gurobi"},
{MPSolver::GLPK_MIXED_INTEGER_PROGRAMMING, "glpk"},
{MPSolver::HIGHS_MIXED_INTEGER_PROGRAMMING, "highs"},
{MPSolver::PDLP_LINEAR_PROGRAMMING, "pdlp"},
{MPSolver::KNAPSACK_MIXED_INTEGER_PROGRAMMING, "knapsack"},
{MPSolver::CPLEX_MIXED_INTEGER_PROGRAMMING, "cplex"},
{MPSolver::XPRESS_MIXED_INTEGER_PROGRAMMING, "xpress"},
};
// static
bool MPSolver::ParseSolverType(absl::string_view solver_id,
MPSolver::OptimizationProblemType* type) {
// Normalize the solver id.
const std::string id =
absl::StrReplaceAll(absl::AsciiStrToUpper(solver_id), {{"-", "_"}});
// Support the full enum name
MPModelRequest::SolverType solver_type;
if (MPModelRequest::SolverType_Parse(id, &solver_type)) {
*type = static_cast<MPSolver::OptimizationProblemType>(solver_type);
return true;
}
// Names are stored in lower case.
std::string lower_id = absl::AsciiStrToLower(id);
// Remove any "_mip" suffix, since they are optional.
if (absl::EndsWith(lower_id, "_mip")) {
lower_id = lower_id.substr(0, lower_id.size() - 4);
}
// Rewrite CP-SAT into SAT.
if (lower_id == "cp_sat") {
lower_id = "sat";
}
// Reverse lookup in the kOptimizationProblemTypeNames[] array.
for (auto& named_solver : kOptimizationProblemTypeNames) {
if (named_solver.name == lower_id) {
*type = named_solver.problem_type;
return true;
}
}
return false;
}
absl::string_view ToString(
MPSolver::OptimizationProblemType optimization_problem_type) {
for (const auto& named_solver : kOptimizationProblemTypeNames) {
if (named_solver.problem_type == optimization_problem_type) {
return named_solver.name;
}
}
LOG(FATAL) << "Unrecognized solver type: "
<< static_cast<int>(optimization_problem_type);
return "";
}
bool AbslParseFlag(const absl::string_view text,
MPSolver::OptimizationProblemType* solver_type,
std::string* error) {
DCHECK(solver_type != nullptr);
DCHECK(error != nullptr);
const bool result = MPSolver::ParseSolverType(text, solver_type);
if (!result) {
*error = absl::StrCat("Solver type: ", text, " does not exist.");
}
return result;
}
/* static */
MPSolver::OptimizationProblemType MPSolver::ParseSolverTypeOrDie(
const std::string& solver_id) {
MPSolver::OptimizationProblemType problem_type;
CHECK(MPSolver::ParseSolverType(solver_id, &problem_type)) << solver_id;
return problem_type;
}
/* static */
MPSolver* MPSolver::CreateSolver(const std::string& solver_id) {
MPSolver::OptimizationProblemType problem_type;
if (!MPSolver::ParseSolverType(solver_id, &problem_type)) {
LOG(WARNING) << "Unrecognized solver type: " << solver_id;
return nullptr;
}
if (!MPSolver::SupportsProblemType(problem_type)) {
LOG(WARNING) << "Support for " << solver_id
<< " not linked in, or the license was not found.";
return nullptr;
}
MPSolver* solver = new MPSolver("", problem_type);
return solver;
}
MPVariable* MPSolver::LookupVariableOrNull(const std::string& var_name) const {
if (!variable_name_to_index_) GenerateVariableNameIndex();
absl::flat_hash_map<std::string, int>::const_iterator it =
variable_name_to_index_->find(var_name);
if (it == variable_name_to_index_->end()) return nullptr;
return variables_[it->second];
}
MPConstraint* MPSolver::LookupConstraintOrNull(
const std::string& constraint_name) const {
if (!constraint_name_to_index_) GenerateConstraintNameIndex();
const auto it = constraint_name_to_index_->find(constraint_name);
if (it == constraint_name_to_index_->end()) return nullptr;
return constraints_[it->second];
}
// ----- Methods using protocol buffers -----
MPSolverResponseStatus MPSolver::LoadModelFromProto(
const MPModelProto& input_model, std::string* error_message,
bool clear_names) {
Clear();
// The variable and constraint names are dropped, because we allow
// duplicate names in the proto (they're not considered as 'ids'),
// unlike the MPSolver C++ API which crashes if there are duplicate names.
// Clearing the names makes the MPSolver generate unique names.
return LoadModelFromProtoInternal(
input_model,
/*name_policy=*/
clear_names ? DEFAULT_CLEAR_NAMES
: INVALID_MODEL_ON_DUPLICATE_NONEMPTY_NAMES,
/*check_model_validity=*/true, error_message);
}
MPSolverResponseStatus MPSolver::LoadModelFromProtoWithUniqueNamesOrDie(
const MPModelProto& input_model, std::string* error_message) {
Clear();
// Force variable and constraint name indexing (which CHECKs name uniqueness).
GenerateVariableNameIndex();
GenerateConstraintNameIndex();
return LoadModelFromProtoInternal(
input_model, /*name_policy=*/DIE_ON_DUPLICATE_NONEMPTY_NAMES,
/*check_model_validity=*/true, error_message);
}
namespace {
// Iterates over all the variable names. See usage.
class MPVariableNamesIterator {
public:
explicit MPVariableNamesIterator(const MPModelProto& model) : model_(model) {}
int index() const { return index_; }
absl::string_view name() const { return model_.variable(index_).name(); }
static std::string DescribeIndex(int index) {
return absl::StrFormat("variable[%d]", index);
}
void Advance() { ++index_; }
bool AtEnd() const { return index_ == model_.variable_size(); }
private:
const MPModelProto& model_;
int index_ = 0;
};
// Iterates over all the constraint and general_constaint names. See usage.
class MPConstraintNamesIterator {
public:
explicit MPConstraintNamesIterator(const MPModelProto& model)
: model_(model),
// To iterate both on the constraint[] and the general_constraint[]
// field, we use the bit trick that i ≥ 0 corresponds to constraint[i],
// and i < 0 corresponds to general_constraint[~i = -i-1].
index_(model_.constraint().empty() ? ~0 : 0) {}
int index() const { return index_; }
absl::string_view name() const {
return index_ >= 0 ? model_.constraint(index_).name()
// As of 2023-04, the only names of MPGeneralConstraints
// that are actually ingested are the
// MPIndicatorConstraint.constraint.name.
: model_.general_constraint(~index_)
.indicator_constraint()
.constraint()
.name();
}
static std::string DescribeIndex(int index) {
return index >= 0
? absl::StrFormat("constraint[%d]", index)
: absl::StrFormat(
"general_constraint[%d].indicator_constraint.constraint",
~index);
}
void Advance() {
if (index_ >= 0) {
if (++index_ == model_.constraint_size()) index_ = ~0;
} else {
--index_;
}
}
bool AtEnd() const { return ~index_ == model_.general_constraint_size(); }
private:
const MPModelProto& model_;
int index_ = 0;
};
// Looks at the `name` field of all the given MPModelProto fields, and if there
// is a duplicate name, returns a descriptive error message.
// If no duplicate is found, returns the empty string.
template <class NameIterator>
std::string FindDuplicateNamesError(NameIterator name_iterator) {
absl::flat_hash_map<absl::string_view, int> name_to_index;
for (; !name_iterator.AtEnd(); name_iterator.Advance()) {
if (name_iterator.name().empty()) continue;
const int index =
name_to_index.insert({name_iterator.name(), name_iterator.index()})
.first->second;
if (index != name_iterator.index()) {
return absl::StrFormat(
"Duplicate name '%s' in %s.name() and %s.name()",
name_iterator.name(), NameIterator::DescribeIndex(index),
NameIterator::DescribeIndex(name_iterator.index()));
}
}
return ""; // No duplicate found.
}
} // namespace
MPSolverResponseStatus MPSolver::LoadModelFromProtoInternal(
const MPModelProto& input_model, ModelProtoNamesPolicy name_policy,
bool check_model_validity, std::string* error_message) {
CHECK(error_message != nullptr);
std::string error;
if (check_model_validity) {
error = FindErrorInMPModelProto(input_model);
}
// We preemptively check for duplicate names even for the
// DIE_ON_DUPLICATE_NONEMPTY_NAMES policy, because it yields more informative
// error messages than if we wait for InsertIfNotPresent() to crash.
if (error.empty() && name_policy != DEFAULT_CLEAR_NAMES) {
error = FindDuplicateNamesError(MPVariableNamesIterator(input_model));
if (error.empty()) {
error = FindDuplicateNamesError(MPConstraintNamesIterator(input_model));
}
if (!error.empty() && name_policy == DIE_ON_DUPLICATE_NONEMPTY_NAMES) {
LOG(FATAL) << error;
}
}
const bool clear_names = name_policy == DEFAULT_CLEAR_NAMES;
if (!error.empty()) {
*error_message = error;
LOG_IF(INFO, OutputIsEnabled())
<< "Invalid model given to LoadModelFromProto(): " << error;
if (absl::GetFlag(FLAGS_mpsolver_bypass_model_validation)) {
LOG_IF(INFO, OutputIsEnabled())
<< "Ignoring the model error(s) because of"
<< " --mpsolver_bypass_model_validation.";
} else {
return absl::StrContains(error, "Infeasible") ? MPSOLVER_INFEASIBLE
: MPSOLVER_MODEL_INVALID;
}
}
if (input_model.has_quadratic_objective()) {
*error_message =
"Optimizing a quadratic objective is only supported through direct "
"proto solves. Please use MPSolver::SolveWithProto, or the solver's "
"direct proto solve function.";
return MPSOLVER_MODEL_INVALID;
}
MPObjective* const objective = MutableObjective();
// Passing empty names makes the MPSolver generate unique names.
const std::string empty;
for (int i = 0; i < input_model.variable_size(); ++i) {
const MPVariableProto& var_proto = input_model.variable(i);
MPVariable* variable =
MakeNumVar(var_proto.lower_bound(), var_proto.upper_bound(),
clear_names ? empty : var_proto.name());
variable->SetInteger(var_proto.is_integer());
if (var_proto.branching_priority() != 0) {
variable->SetBranchingPriority(var_proto.branching_priority());
}
objective->SetCoefficient(variable, var_proto.objective_coefficient());
}
for (const MPConstraintProto& ct_proto : input_model.constraint()) {
if (ct_proto.lower_bound() == -infinity() &&
ct_proto.upper_bound() == infinity()) {
continue;
}
MPConstraint* const ct =
MakeRowConstraint(ct_proto.lower_bound(), ct_proto.upper_bound(),
clear_names ? empty : ct_proto.name());
ct->set_is_lazy(ct_proto.is_lazy());
for (int j = 0; j < ct_proto.var_index_size(); ++j) {
ct->SetCoefficient(variables_[ct_proto.var_index(j)],
ct_proto.coefficient(j));
}
}
for (const MPGeneralConstraintProto& general_constraint :
input_model.general_constraint()) {
switch (general_constraint.general_constraint_case()) {
case MPGeneralConstraintProto::kIndicatorConstraint: {
const auto& proto =
general_constraint.indicator_constraint().constraint();
if (proto.lower_bound() == -infinity() &&
proto.upper_bound() == infinity()) {
continue;
}
const int constraint_index = NumConstraints();
MPConstraint* const constraint = new MPConstraint(
constraint_index, proto.lower_bound(), proto.upper_bound(),
clear_names ? "" : proto.name(), interface_.get());
if (constraint_name_to_index_) {
gtl::InsertOrDie(&*constraint_name_to_index_, constraint->name(),
constraint_index);
}
constraints_.push_back(constraint);
constraint_is_extracted_.push_back(false);
constraint->set_is_lazy(proto.is_lazy());
for (int j = 0; j < proto.var_index_size(); ++j) {
constraint->SetCoefficient(variables_[proto.var_index(j)],
proto.coefficient(j));
}
MPVariable* const variable =
variables_[general_constraint.indicator_constraint().var_index()];
constraint->indicator_variable_ = variable;
constraint->indicator_value_ =
general_constraint.indicator_constraint().var_value();
if (!interface_->AddIndicatorConstraint(constraint)) {
*error_message = "Solver doesn't support indicator constraints";
return MPSOLVER_MODEL_INVALID;
}
break;
}
default:
*error_message = absl::StrFormat(
"Optimizing general constraints of type %i is only supported "
"through direct proto solves. Please use MPSolver::SolveWithProto, "
"or the solver's direct proto solve function.",
general_constraint.general_constraint_case());
return MPSOLVER_MODEL_INVALID;
}
}
objective->SetOptimizationDirection(input_model.maximize());
if (input_model.has_objective_offset()) {
objective->SetOffset(input_model.objective_offset());
}
// Stores any hints about where to start the solve.
solution_hint_.clear();
for (int i = 0; i < input_model.solution_hint().var_index_size(); ++i) {
solution_hint_.push_back(
std::make_pair(variables_[input_model.solution_hint().var_index(i)],
input_model.solution_hint().var_value(i)));
}
return MPSOLVER_MODEL_IS_VALID;
}
namespace {
MPSolverResponseStatus ResultStatusToMPSolverResponseStatus(
MPSolver::ResultStatus status) {
switch (status) {
case MPSolver::OPTIMAL:
return MPSOLVER_OPTIMAL;
case MPSolver::FEASIBLE:
return MPSOLVER_FEASIBLE;
case MPSolver::INFEASIBLE:
return MPSOLVER_INFEASIBLE;
case MPSolver::UNBOUNDED:
return MPSOLVER_UNBOUNDED;
case MPSolver::ABNORMAL:
return MPSOLVER_ABNORMAL;
case MPSolver::MODEL_INVALID:
return MPSOLVER_MODEL_INVALID;
case MPSolver::NOT_SOLVED:
return MPSOLVER_NOT_SOLVED;
}
return MPSOLVER_UNKNOWN_STATUS;
}
} // namespace
void MPSolver::FillSolutionResponseProto(MPSolutionResponse* response) const {
CHECK(response != nullptr);
response->Clear();
response->set_status(
ResultStatusToMPSolverResponseStatus(interface_->result_status_));
response->mutable_solve_info()->set_solve_wall_time_seconds(wall_time() /
1000.0);
if (interface_->result_status_ == MPSolver::OPTIMAL ||
interface_->result_status_ == MPSolver::FEASIBLE) {
response->set_objective_value(Objective().Value());
for (MPVariable* variable : variables_) {
response->add_variable_value(variable->solution_value());
}
if (interface_->IsMIP()) {
response->set_best_objective_bound(interface_->best_objective_bound());
} else {
// Dual values have no meaning in MIP.
for (MPConstraint* constraint : constraints_) {
response->add_dual_value(constraint->dual_value());
}
// Reduced cost have no meaning in MIP.
for (MPVariable* variable : variables_) {
response->add_reduced_cost(variable->reduced_cost());
}
}
}
}
namespace {
bool InCategory(int status, int category) {
if (category == MPSOLVER_OPTIMAL) return status == MPSOLVER_OPTIMAL;