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// Copyright (c) 2018-2024 Charlie Vanaret
// Licensed under the MIT license. See LICENSE file in the project directory for details.
#include "Uno.hpp"
#include "ingredients/constraint_relaxation_strategies/ConstraintRelaxationStrategyFactory.hpp"
#include "ingredients/globalization_mechanisms/GlobalizationMechanismFactory.hpp"
#include "ingredients/globalization_strategies/GlobalizationStrategyFactory.hpp"
#include "ingredients/hessian_models/HessianModelFactory.hpp"
#include "ingredients/inequality_handling_methods/InequalityHandlingMethodFactory.hpp"
#include "ingredients/inertia_correction_strategies/InertiaCorrectionStrategyFactory.hpp"
#include "ingredients/subproblem_solvers/QPSolverFactory.hpp"
#include "ingredients/subproblem_solvers/LPSolverFactory.hpp"
#include "ingredients/subproblem_solvers/SymmetricIndefiniteLinearSolverFactory.hpp"
#include "../interfaces/C/Uno_C_API.h"
#include "linear_algebra/Vector.hpp"
#include "model/BoundRelaxedModel.hpp"
#include "model/FixedBoundsConstraintsModel.hpp"
#include "model/HomogeneousEqualityConstrainedModel.hpp"
#include "model/Model.hpp"
#include "optimization/EvaluationCache.hpp"
#include "optimization/Iterate.hpp"
#include "optimization/WarmstartInformation.hpp"
#include "tools/Logger.hpp"
#include "optimization/OptimizationStatus.hpp"
#include "options/Options.hpp"
#include "tools/Statistics.hpp"
#include "tools/Timer.hpp"
#include "tools/UserCallbacks.hpp"
namespace uno {
Level Logger::level = INFO;
// solve without user callbacks
Result Uno::solve(const Model& model, Options& options) {
// pass user callbacks that do nothing
NoUserCallbacks user_callbacks{};
return this->solve(model, options, user_callbacks);
}
// solve with user callbacks
Result Uno::solve(const Model& model, Options& options, UserCallbacks& user_callbacks) {
DISCRETE << "Original model " << model.name << '\n' << model.number_variables << " variables, " <<
model.number_constraints << " constraints (" << model.get_equality_constraints().size() <<
" equality, " << model.get_inequality_constraints().size() << " inequality)\n";
INFO << "Problem type: " << to_string(model.get_problem_type()) << '\n';
// reformulate the model if it is to be solved with an interior-point method with log barrier function
if (options.get_string("inequality_handling_method") == "interior_point" && options.get_string("barrier_function") == "log") {
// move the fixed variables to the set of general constraints
const FixedBoundsConstraintsModel fixed_bound_model(model);
// if an equality-constrained problem is required (e.g. interior points or AL), reformulate the model with slacks
const HomogeneousEqualityConstrainedModel homogeneous_model(fixed_bound_model);
// slightly relax the bound constraints
const BoundRelaxedModel bound_relaxed_model(homogeneous_model, options);
DISCRETE << "Reformulated model " << bound_relaxed_model.name << '\n' << bound_relaxed_model.number_variables << " variables, " <<
bound_relaxed_model.number_constraints << " constraints (" << bound_relaxed_model.get_equality_constraints().size() <<
" equality, " << bound_relaxed_model.get_inequality_constraints().size() << " inequality)\n";
Result result = uno_solve(bound_relaxed_model, options, user_callbacks);
// fix the dimensions
result.number_variables = model.number_variables;
result.number_constraints = model.number_constraints;
return result;
}
else {
return uno_solve(model, options, user_callbacks);
}
}
// protected solve function
Result Uno::uno_solve(const Model& model, Options& options, UserCallbacks& user_callbacks) {
const Timer timer{};
size_t major_iterations = 0;
// initialize initial primal and dual points
Iterate current_iterate(model.number_variables, model.number_constraints);
model.initial_primal_point(current_iterate.primals);
model.initial_dual_point(current_iterate.multipliers.constraints);
model.reset_number_evaluations();
EvaluationCache evaluation_cache{model};
Statistics statistics = Uno::create_statistics(model);
WarmstartInformation warmstart_information{};
warmstart_information.whole_problem_changed();
OptimizationStatus optimization_status = OptimizationStatus::SUCCESS;
try { // catch errors at startup/initial iterate
// set the ingredients based on the user-defined options
this->globalization_mechanism = GlobalizationMechanismFactory::create(model, options);
// use the initial primal-dual point to initialize the strategies and generate the initial iterate
this->initialize(statistics, model, current_iterate, options, evaluation_cache);
// allocate the trial iterate once and for all here
Iterate trial_iterate(current_iterate);
try { // catch errors during the optimization process
bool termination = false;
const size_t max_iterations = options.get_unsigned_int("max_iterations"); // maximum number of iterations
const double time_limit = options.get_double("time_limit"); // CPU time limit (can be inf)
if (max_iterations == 0) {
termination = true;
optimization_status = OptimizationStatus::ITERATION_LIMIT;
}
// outer loop: compute a sequence of accepted iterates
while (!termination) {
++major_iterations;
statistics.start_new_line();
statistics.set("Major", major_iterations);
DEBUG << "\n### Outer iteration " << major_iterations << '\n';
// compute an acceptable iterate by solving a subproblem at the current point
warmstart_information.iterate_changed();
this->globalization_mechanism->compute_next_iterate(statistics, model, current_iterate, trial_iterate,
this->direction, evaluation_cache, warmstart_information, user_callbacks);
const bool user_termination = user_callbacks.user_termination(trial_iterate.primals, trial_iterate.multipliers,
trial_iterate.objective_multiplier, trial_iterate.progress.infeasibility, trial_iterate.residuals.stationarity,
trial_iterate.residuals.complementarity);
termination = Uno::check_termination(trial_iterate.status, major_iterations, max_iterations,
timer.get_duration(), time_limit, user_termination, optimization_status);
// the trial iterate becomes the current iterate for the next iteration
std::swap(current_iterate, trial_iterate);
std::swap(evaluation_cache.current_evaluations, evaluation_cache.trial_evaluations);
evaluation_cache.trial_evaluations.reset();
}
}
catch (std::exception& exception) {
statistics.start_new_line();
statistics.set("Status", exception.what());
if (Logger::level == INFO) statistics.print_current_line();
DEBUG << exception.what() << '\n';
optimization_status = OptimizationStatus::ALGORITHMIC_ERROR;
}
if (Logger::level == INFO) statistics.print_footer();
Uno::postprocess_solution(model, current_iterate, evaluation_cache.current_evaluations);
}
catch (const std::exception& e) {
DISCRETE << "An error occurred at the initial iterate: " << e.what() << '\n';
optimization_status = OptimizationStatus::EVALUATION_ERROR;
}
Result result = this->create_result(model, optimization_status, current_iterate, evaluation_cache.current_evaluations,
major_iterations, timer);
Uno::postprocess_multipliers_signs(model, result);
this->print_optimization_summary(result, options.get_bool("print_solution"));
return result;
}
std::string Uno::current_version() {
return std::to_string(UNO_VERSION_MAJOR) + "." + std::to_string(UNO_VERSION_MINOR) + "." + std::to_string(UNO_VERSION_PATCH);
}
void Uno::print_available_strategies() {
std::cout << "Available Uno strategies:\n";
std::cout << "- Constraint relaxation strategies: " << join(ConstraintRelaxationStrategyFactory::available_strategies, ", ") << '\n';
std::cout << "- Globalization mechanisms: " << join(GlobalizationMechanismFactory::available_strategies, ", ") << '\n';
std::cout << "- Globalization strategies: " << join(GlobalizationStrategyFactory::available_strategies, ", ") << '\n';
std::cout << "- Inequality handling methods: " << join(InequalityHandlingMethodFactory::available_strategies(), ", ") << '\n';
std::cout << "- Hessian models: " << join(HessianModelFactory::available_strategies, ", ") << '\n';
std::cout << "- Inertia correction strategies: " << join(InertiaCorrectionStrategyFactory::available_strategies, ", ") << '\n';
std::cout << "- QP solvers: " << join(QPSolverFactory::available_solvers, ", ") << '\n';
std::cout << "- LP solvers: " << join(LPSolverFactory::available_solvers, ", ") << '\n';
std::cout << "- Linear solvers: " << join(SymmetricIndefiniteLinearSolverFactory::available_solvers(), ", ") << '\n';
std::cout << "- Presets: filtersqp, ipopt\n";
}
void Uno::initialize(Statistics& statistics, const Model& model, Iterate& current_iterate, const Options& options,
EvaluationCache& evaluation_cache) {
statistics.start_new_line();
statistics.set("Major", 0);
statistics.set("Status", "initial point");
model.project_onto_variable_bounds(current_iterate.primals);
this->globalization_mechanism->initialize(statistics, model, current_iterate, this->direction, evaluation_cache, options);
options.print_non_default();
if (Logger::level == INFO) {
statistics.print_header();
statistics.print_current_line();
}
}
Statistics Uno::create_statistics(const Model& model) {
Statistics statistics{};
statistics.add_column("Major", Statistics::int_width, 3, Statistics::column_order.at("Major"));
statistics.add_column("||Step||", Statistics::double_width, 2, Statistics::column_order.at("||Step||"));
statistics.add_column("Objective", Statistics::double_width + 1, 3, Statistics::column_order.at("Objective"));
if (model.is_constrained()) {
statistics.add_column("Infeas", Statistics::double_width, 2, Statistics::column_order.at("Infeas"));
}
statistics.add_column("Statio", Statistics::double_width, 2, Statistics::column_order.at("Statio"));
statistics.add_column("Compl", Statistics::double_width, 2, Statistics::column_order.at("Compl"));
statistics.add_column("Status", Statistics::string_width, 3, Statistics::column_order.at("Status"));
return statistics;
}
bool Uno::check_termination(SolutionStatus solution_status, size_t iteration, size_t max_iterations, double current_time,
double time_limit, bool user_termination, OptimizationStatus& optimization_status) {
if (solution_status != SolutionStatus::NOT_OPTIMAL) {
return true;
}
else if (max_iterations <= iteration) {
optimization_status = OptimizationStatus::ITERATION_LIMIT;
return true;
}
else if (time_limit <= current_time) {
optimization_status = OptimizationStatus::TIME_LIMIT;
return true;
}
else if (user_termination) {
optimization_status = OptimizationStatus::USER_TERMINATION;
return true;
}
return false;
}
void Uno::postprocess_solution(const Model& model, Iterate& iterate, Evaluations& evaluations) {
// in case the objective was not yet evaluated, evaluate it
evaluations.evaluate_objective(model, iterate.primals);
model.postprocess_solution(iterate);
DEBUG2 << "Final iterate:\n" << iterate;
}
Result Uno::create_result(const Model& model, OptimizationStatus optimization_status, const Iterate& solution,
const Evaluations& evaluations, size_t major_iterations, const Timer& timer) const {
const size_t number_subproblems_solved = (this->globalization_mechanism != nullptr) ?
this->globalization_mechanism->get_number_subproblems_solved() : 0;
return {model.number_variables, model.number_constraints, optimization_status, solution.status,
evaluations.objective, solution.progress.infeasibility, solution.residuals.stationarity,
solution.residuals.complementarity, solution.primals, solution.multipliers.constraints,
solution.multipliers.lower_bounds, solution.multipliers.upper_bounds, major_iterations, timer.get_duration(),
model.number_model_objective_evaluations(), model.number_model_constraints_evaluations(),
model.number_model_objective_gradient_evaluations(), model.number_model_jacobian_evaluations(),
model.number_model_hessian_evaluations(), number_subproblems_solved};
}
// flip the signs of the multipliers, depending on what the sign convention of the Lagrangian is, and whether
// we maximize
void Uno::postprocess_multipliers_signs(const Model& model, Result& result) {
if ((model.optimization_sense == 1. && model.lagrangian_sign_convention == -1.) ||
(model.optimization_sense == -1. && model.lagrangian_sign_convention == 1.)) {
// do nothing
}
else {
// change the signs of the multipliers
result.constraint_dual_solution.scale(-1.);
result.lower_bound_dual_solution.scale(-1.);
result.upper_bound_dual_solution.scale(-1.);
}
result.solution_objective *= model.optimization_sense;
}
std::string Uno::get_strategy_combination() const {
return (this->globalization_mechanism != nullptr) ? this->globalization_mechanism->get_name() :
"strategy combination not initialized";
}
void Uno::print_optimization_summary(const Result& result, bool print_solution) const {
DISCRETE << "\nUno " << Uno::current_version() << " (" << this->get_strategy_combination() << ")\n";
DISCRETE << Timer::get_current_date();
DISCRETE << "────────────────────────────────────────\n";
result.print(print_solution);
}
} // namespace