ortools-clone/linear_solver/clp_interface.cc

// Copyright 2010-2011 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 <algorithm>
#include "base/hash.h"
#include <string>
#include <vector>

#include "base/commandlineflags.h"
#include "base/integral_types.h"
#include "base/logging.h"
#include "base/scoped_ptr.h"
#include "base/stringprintf.h"
#include "base/timer.h"
#include "base/strutil.h"
#include "base/concise_iterator.h"
#include "base/hash.h"
#include "linear_solver/linear_solver.h"

#if defined(USE_CLP) || defined(USE_CBC)

#undef PACKAGE
#undef VERSION
#include "coin/ClpSimplex.hpp"
#include "coin/CoinBuild.hpp"
#include "coin/ClpMessage.hpp"

#if defined(_MSC_VER)
#include "coin/configall_system.h"
#else
#include "coin/config_clp.h"
#endif

DECLARE_double(solver_timeout_in_seconds);
DECLARE_string(solver_write_model);

namespace operations_research {

class CLPInterface : public MPSolverInterface {
 public:
  // Constructor that takes a name for the underlying CLP solver.
  explicit CLPInterface(MPSolver* const solver);
  ~CLPInterface();

  // Sets the optimization direction (min/max).
  virtual void SetOptimizationDirection(bool maximize);

  // ----- Solve -----
  // Solve the problem using the parameter values specified.
  virtual MPSolver::ResultStatus Solve(const MPSolverParameters& param);

  // ----- Model modifications and extraction -----
  // Resets extracted model
  virtual void Reset();

  // Modify bounds.
  virtual void SetVariableBounds(int var_index, double lb, double ub);
  virtual void SetVariableInteger(int var_index, bool integer);
  virtual void SetConstraintBounds(int row_index, double lb, double ub);

  // Add constraint incrementally.
  void AddRowConstraint(MPConstraint* const ct);
  // Add variable incrementally.
  void AddVariable(MPVariable* const var);
  // Change a coefficient in a constraint.
  virtual void SetCoefficient(MPConstraint* const constraint,
                              MPVariable* const variable,
                              double new_value,
                              double old_value);
  // Clear a constraint from all its terms.
  virtual void ClearConstraint(MPConstraint* const constraint);

  // Change a coefficient in the linear objective.
  virtual void SetObjectiveCoefficient(MPVariable* const variable,
                                       double coefficient);
  // Change the constant term in the linear objective.
  virtual void SetObjectiveOffset(double value);
  // Clear the objective from all its terms.
  virtual void ClearObjective();

  // ------ Query statistics on the solution and the solve ------
  // Number of simplex iterations
  virtual int64 iterations() const;
  // Number of branch-and-bound nodes. Only available for discrete problems.
  virtual int64 nodes() const;
  // Best objective bound. Only available for discrete problems.
  virtual double best_objective_bound() const;

  // ----- Misc -----
  // Write model
  virtual void WriteModel(const string& filename);

  // Query problem type.
  virtual bool IsContinuous() const { return true; }
  virtual bool IsLP() const { return true; }
  virtual bool IsMIP() const { return false; }

  virtual void ExtractNewVariables();
  virtual void ExtractNewConstraints();
  virtual void ExtractObjective();

  virtual string SolverVersion() const {
    return PACKAGE_STRING;
  }

  virtual void* underlying_solver() {
    return reinterpret_cast<void*>(clp_.get());
  }

 private:
  // Create dummy variable to be able to create empty constraints.
  void CreateDummyVariableForEmptyConstraints();

  // Set all parameters in the underlying solver.
  virtual void SetParameters(const MPSolverParameters& param);
  // Set each parameter in the underlying solver.
  virtual void SetRelativeMipGap(double value);
  virtual void SetPresolveMode(int value);
  virtual void SetLpAlgorithm(int value);

  scoped_ptr<ClpSimplex> clp_;  // TODO(user) : remove pointer.
  scoped_ptr<ClpSolve> options_;  // For parameter setting.
};

// ----- Solver -----

// Creates a LP/MIP instance with the specified name and minimization objective.
CLPInterface::CLPInterface(MPSolver* const solver)
    : MPSolverInterface(solver),
      clp_(new ClpSimplex), options_(new ClpSolve) {
    clp_->setStrParam(ClpProbName, solver_->name_);
    clp_->setOptimizationDirection(1);
}

CLPInterface::~CLPInterface() {}

void CLPInterface::Reset() {
  clp_.reset(new ClpSimplex);
  clp_->setOptimizationDirection(maximize_ ? -1 : 1);
  ResetExtractionInformation();
}

void CLPInterface::WriteModel(const string& filename) {
  // CLP does not support the LP format natively. It only supports it
  // through OsiClpSolverInterface.
  // TODO(user) : Implement support for .lp format.
  if (HasSuffixString(filename, ".lp")) {
    LOG(WARNING) << "CLP does not support the LP format, "
                 << "writing in MPS format instead.";
  }
  clp_->writeMps(filename.c_str());
}

// ------ Model modifications and extraction -----

// Not cached
void CLPInterface::SetOptimizationDirection(bool maximize) {
  InvalidateSolutionSynchronization();
  clp_->setOptimizationDirection(maximize ? -1 : 1);
}

void CLPInterface::SetVariableBounds(int var_index, double lb, double ub) {
  InvalidateSolutionSynchronization();
  if (var_index != kNoIndex) {
    // Not cached if the variable has been extracted
    DCHECK_LE(var_index, last_variable_index_);
    clp_->setColumnBounds(var_index, lb, ub);
  } else {
    sync_status_ = MUST_RELOAD;
  }
}

// Ignore as CLP does not solve models with integer variables
void CLPInterface::SetVariableInteger(int var_index, bool integer) {}

void CLPInterface::SetConstraintBounds(int index, double lb, double ub) {
  InvalidateSolutionSynchronization();
  if (index != kNoIndex) {
    // Not cached if the row has been extracted
    DCHECK_LE(index, last_constraint_index_);
    clp_->setRowBounds(index, lb, ub);
  } else {
    sync_status_ = MUST_RELOAD;
  }
}

void CLPInterface::SetCoefficient(MPConstraint* const constraint,
                                  MPVariable* const variable,
                                  double new_value,
                                  double old_value) {
  InvalidateSolutionSynchronization();
  const int constraint_index = constraint->index();
  const int variable_index = variable->index();
  if (constraint_index != kNoIndex && variable_index != kNoIndex) {
    // The modification of the coefficient for an extracted row and
    // variable is not cached.
    DCHECK_LE(constraint_index, last_constraint_index_);
    DCHECK_LE(variable_index, last_variable_index_);
    clp_->modifyCoefficient(constraint_index, variable_index, new_value);
  } else {
    // The modification of an unextracted row or variable is cached
    // and handled in ExtractModel.
    sync_status_ = MUST_RELOAD;
  }
}

// Not cached
void CLPInterface::ClearConstraint(MPConstraint* const constraint) {
  InvalidateSolutionSynchronization();
  const int constraint_index = constraint->index();
  // Constraint may not have been extracted yet.
  if (constraint_index != kNoIndex) {
    for (ConstIter<hash_map<MPVariable*, double> >
             it(constraint->coefficients_); !it.at_end(); ++it) {
      const int var_index = it->first->index();
      DCHECK_NE(kNoIndex, var_index);
      clp_->modifyCoefficient(constraint_index, var_index, 0.0);
    }
  }
}

// Cached
void CLPInterface::SetObjectiveCoefficient(MPVariable* const variable,
                                           double coefficient) {
  sync_status_ = MUST_RELOAD;
}

// Cached
void CLPInterface::SetObjectiveOffset(double value) {
  sync_status_ = MUST_RELOAD;
}

// Clear objective of all its terms.
void CLPInterface::ClearObjective() {
  InvalidateSolutionSynchronization();
  // Clear linear terms
  for (ConstIter<hash_map<MPVariable*, double> >
           it(solver_->linear_objective_.coefficients_);
       !it.at_end(); ++it) {
    const int var_index = it->first->index();
    // Variable may have not been extracted yet.
    if (var_index == kNoIndex) {
      DCHECK_NE(MODEL_SYNCHRONIZED, sync_status_);
    } else {
      clp_->setObjectiveCoefficient(var_index, 0.0);
    }
  }
  // Clear constant term.
  clp_->setObjectiveOffset(0.0);
}

void CLPInterface::AddRowConstraint(MPConstraint* const ct) {
  sync_status_ = MUST_RELOAD;
}

void CLPInterface::AddVariable(MPVariable* const var) {
  sync_status_ = MUST_RELOAD;
}

void CLPInterface::CreateDummyVariableForEmptyConstraints() {
  clp_->setColumnBounds(kDummyVariableIndex, 0.0, 0.0);
  clp_->setObjectiveCoefficient(kDummyVariableIndex, 0.0);
  // Workaround for peculiar signature of setColumnName.
  std::string dummy_name = "dummy";
  int var_index = kDummyVariableIndex;
  clp_->setColumnName(var_index, dummy_name);
}

// Define new variables and add them to existing constraints.
void CLPInterface::ExtractNewVariables() {
  // Define new variables
  int total_num_vars = solver_->variables_.size();
  if (total_num_vars > last_variable_index_) {
    if (last_variable_index_ == 0 && last_constraint_index_ == 0) {
      // Faster extraction when nothing has been extracted yet.
      clp_->resize(0, total_num_vars + 1);
      CreateDummyVariableForEmptyConstraints();
      for (int i = 0; i < total_num_vars; ++i) {
        MPVariable* const var = solver_->variables_[i];
        int var_index = i + 1;  // offset by 1 because of dummy variable.
        var->set_index(var_index);
        if (!var->name().empty()) {
          std::string std_name = var->name();
          clp_->setColumnName(var_index, std_name);
        }
        clp_->setColumnBounds(var_index, var->lb(), var->ub());
      }
    } else {
      // TODO(user): This could perhaps be made slightly faster by
      // iterating through old constraints, constructing by hand the
      // column-major representation of the addition to them and call
      // clp_->addColumns. But this is good enough for now.
      // Create new variables.
      for (int j = last_variable_index_; j < total_num_vars; ++j) {
        MPVariable* const var = solver_->variables_[j];
        DCHECK_EQ(kNoIndex, var->index());
        int var_index = j + 1;  // offset by 1 because of dummy variable.
        var->set_index(var_index);
        // The true objective coefficient will be set later in ExtractObjective.
        double tmp_obj_coef = 0.0;
        clp_->addColumn(0, NULL, NULL, var->lb(), var->ub(), tmp_obj_coef);
        if (!var->name().empty()) {
          std::string std_name = var->name();
          clp_->setColumnName(var_index, std_name);
        }
      }
      // Add new variables to existing constraints.
      for (int i = 0; i < last_constraint_index_; i++) {
        MPConstraint* const ct = solver_->constraints_[i];
        for (ConstIter<hash_map<MPVariable*, double> > it(ct->coefficients_);
             !it.at_end(); ++it) {
          const int var_index = it->first->index();
          DCHECK_NE(kNoIndex, var_index);
          if (var_index >= last_variable_index_) {
            clp_->modifyCoefficient(i, var_index, it->second);
          }
        }
      }
    }
  }
}

// Define new constraints on old and new variables.
void CLPInterface::ExtractNewConstraints() {
  int total_num_rows = solver_->constraints_.size();
  if (last_constraint_index_ < total_num_rows) {
    // Find the length of the longest row.
    int max_row_length = 0;
    for (int i = last_constraint_index_; i < total_num_rows; ++i) {
      MPConstraint* const ct = solver_->constraints_[i];
      DCHECK_EQ(kNoIndex, ct->index());
      ct->set_index(i);
      if (ct->coefficients_.size() > max_row_length) {
        max_row_length = ct->coefficients_.size();
      }
    }
    // Make space for dummy variable.
    max_row_length = std::max(1, max_row_length);
    scoped_array<int> indices(new int[max_row_length]);
    scoped_array<double> coefs(new double[max_row_length]);
    CoinBuild build_object;
    // Add each new constraint.
    for (int i = last_constraint_index_; i < total_num_rows; ++i) {
      MPConstraint* const  ct = solver_->constraints_[i];
      DCHECK_NE(kNoIndex, ct->index());
      int size = ct->coefficients_.size();
      if (size == 0) {
        // Add dummy variable to be able to build the constraint.
        indices[0] = kDummyVariableIndex;
        coefs[0] = 1.0;
        size = 1;
      }
      int j = 0;
      for (ConstIter<hash_map<MPVariable*, double> > it(ct->coefficients_);
           !it.at_end(); ++it) {
        const int index = it->first->index();
        DCHECK_NE(kNoIndex, index);
        indices[j] = index;
        coefs[j] = it->second;
        j++;
      }
      build_object.addRow(size,
                          indices.get(),
                          coefs.get(),
                          ct->lb(),
                          ct->ub());
    }
    // Add and name the rows.
    clp_->addRows(build_object);
    for (int i = last_constraint_index_; i < total_num_rows; ++i) {
      MPConstraint* const ct = solver_->constraints_[i];
      if (!ct->name().empty()) {
        std::string std_name = ct->name();
        clp_->setRowName(ct->index(), std_name);
      }
    }
  }
}

void CLPInterface::ExtractObjective() {
  // Linear objective: set objective coefficients for all variables
  // (some might have been modified)
  for (ConstIter<hash_map<MPVariable*, double> >
           it(solver_->linear_objective_.coefficients_);
       !it.at_end(); ++it) {
    clp_->setObjectiveCoefficient(it->first->index(), it->second);
  }

  // Constant term. Use -offset instead of +offset because CLP does
  // not follow conventions.
  clp_->setObjectiveOffset(-solver_->linear_objective_.offset_);
}

// Extracts model and solve the LP/MIP. Returns the status of the search.
MPSolver::ResultStatus CLPInterface::Solve(const MPSolverParameters& param) {
  WallTimer timer;
  timer.Start();

  // Set log level.
  CoinMessageHandler message_handler;
  clp_->passInMessageHandler(&message_handler);
  if (quiet_) {
    message_handler.setLogLevel(1, 0);
    clp_->setLogLevel(0);
  } else {
    message_handler.setLogLevel(1, 1);
    clp_->setLogLevel(1);
  }

  // Special case if the model is empty since CLP is not able to
  // handle this special case by itself.
  if (solver_->variables_.size() == 0 && solver_->constraints_.size() == 0) {
    sync_status_ = SOLUTION_SYNCHRONIZED;
    result_status_ = MPSolver::OPTIMAL;
    objective_value_ = solver_->linear_objective_.offset_;
    return result_status_;
  }

  ExtractModel();
  VLOG(1) << StringPrintf("Model built in %.3f seconds.", timer.Get());

  WriteModelToPredefinedFiles();

  // Time limit.
  if (solver_->time_limit()) {
    VLOG(1) << "Setting time limit = " << solver_->time_limit() << " ms.";
    clp_->setMaximumSeconds(solver_->time_limit() / 1000.0);
  } else {
    clp_->setMaximumSeconds(-1.0);
  }

  // Start from a fresh set of default parameters and set them to
  // specified values.
  options_.reset(new ClpSolve);
  SetParameters(param);

  // Solve
  timer.Restart();
  clp_->initialSolve(*options_);
  VLOG(1) << StringPrintf("Solved in %.3f seconds.", timer.Get());

  // Get the results
  objective_value_ = clp_->objectiveValue();
  VLOG(1) << "objective=" << objective_value_;
  const double* const values = clp_->getColSolution();
  const double* const reduced_costs = clp_->getReducedCost();
  for (int i = 0; i < solver_->variables_.size(); ++i) {
    MPVariable* const var = solver_->variables_[i];
    const int var_index = var->index();
    double val = values[var_index];
    var->set_solution_value(val);
    VLOG(3) << var->name() << ": value = " << val;
    double reduced_cost = reduced_costs[var_index];
    var->set_reduced_cost(reduced_cost);
    VLOG(4) << var->name() << ": reduced cost = " << reduced_cost;
  }
  const double* const dual_values = clp_->getRowPrice();
  const double* const row_activities = clp_->getRowActivity();
  for (int i = 0; i < solver_->constraints_.size(); ++i) {
    MPConstraint* const ct = solver_->constraints_[i];
    const int constraint_index = ct->index();
    const double row_activity = row_activities[constraint_index];
    ct->set_activity(row_activity);
    const double dual_value = dual_values[constraint_index];
    ct->set_dual_value(dual_value);
    VLOG(4) << "row " << ct->index()
            << ": activity = " << row_activity
            << " dual value = " << dual_value;
  }

  // Check the status: optimal, infeasible, etc.
  int tmp_status = clp_->status();
  VLOG(1) << "clp result status: " << tmp_status;
  switch (tmp_status) {
    case CLP_SIMPLEX_FINISHED:
      result_status_ = MPSolver::OPTIMAL;
      break;
    case CLP_SIMPLEX_INFEASIBLE:
      result_status_ = MPSolver::INFEASIBLE;
      break;
    case CLP_SIMPLEX_UNBOUNDED:
      result_status_ = MPSolver::UNBOUNDED;
      break;
    case CLP_SIMPLEX_STOPPED:
      result_status_ = MPSolver::FEASIBLE;
      break;
    default:
      result_status_ = MPSolver::ABNORMAL;
      break;
  }

  sync_status_ = SOLUTION_SYNCHRONIZED;
  return result_status_;
}

MPSolverInterface* BuildCLPInterface(MPSolver* const solver) {
  return new CLPInterface(solver);
}

// ------ Query statistics on the solution and the solve ------

int64 CLPInterface::iterations() const {
  CheckSolutionIsSynchronized();
  return clp_->getIterationCount();
}

int64 CLPInterface::nodes() const {
  LOG(FATAL) << "Number of nodes only available for discrete problems";
  return kUnknownNumberOfNodes;
}

double CLPInterface::best_objective_bound() const {
  LOG(FATAL) << "Best objective bound only available for discrete problems";
  return 0.0;
}

// ------ Parameters ------

void CLPInterface::SetParameters(const MPSolverParameters& param) {
  SetCommonParameters(param);
}

void CLPInterface::SetRelativeMipGap(double value) {
  LOG(WARNING) << "The relative MIP gap is only available "
               << "for discrete problems.";
}

void CLPInterface::SetPresolveMode(int value) {
  switch (value) {
    case MPSolverParameters::PRESOLVE_OFF: {
      options_->setPresolveType(ClpSolve::presolveOff);
      break;
    }
    case MPSolverParameters::PRESOLVE_ON: {
      options_->setPresolveType(ClpSolve::presolveOn);
      break;
    }
    default: {
      SetIntegerParamToUnsupportedValue(MPSolverParameters::PRESOLVE, value);
    }
  }
}

void CLPInterface::SetLpAlgorithm(int value) {
  switch (value) {
    case MPSolverParameters::DUAL: {
      options_->setSolveType(ClpSolve::useDual);
      break;
    }
    case MPSolverParameters::PRIMAL: {
      options_->setSolveType(ClpSolve::usePrimal);
      break;
    }
    case MPSolverParameters::BARRIER: {
      options_->setSolveType(ClpSolve::useBarrier);
      break;
    }
    default: {
      SetIntegerParamToUnsupportedValue(MPSolverParameters::LP_ALGORITHM,
                                        value);
    }
  }
}

}  // namespace operations_research
#endif  // #if defined(USE_CBC) || defined(USE_CLP)