remove MPSolver::*Objective* setters, getters, use setters/getters on objective

examples/com/google/ortools/linearsolver/samples/IntegerProgramming.java

@@ -54,8 +54,8 @@ public class IntegerProgramming {
     MPVariable x2 = solver.makeIntVar(0.0, infinity, "x2");
 
     // Minimize x1 + 2 * x2.
-    solver.setObjectiveCoefficient(x1, 1);
-    solver.setObjectiveCoefficient(x2, 2);
+    solver.objective().setCoefficient(x1, 1);
+    solver.objective().setCoefficient(x2, 2);
 
     // 2 * x2 + 3 * x1 >= 17.
     MPConstraint ct = solver.makeConstraint(17, infinity);
@@ -75,7 +75,7 @@ public class IntegerProgramming {
 
     // The objective value of the solution.
     System.out.println("Optimal objective value = " +
-                       solver.objectiveValue());
+                       solver.objective().value());
 
     // The value of each variable in the solution.
     System.out.println("x1 = " + x1.solutionValue());

examples/com/google/ortools/linearsolver/samples/LinearProgramming.java

@@ -55,10 +55,10 @@ public class LinearProgramming {
     MPVariable x3 = solver.makeNumVar(0.0, infinity, "x3");
 
     // Maximize 10 * x1 + 6 * x2 + 4 * x3.
-    solver.setObjectiveCoefficient(x1, 10);
-    solver.setObjectiveCoefficient(x2, 6);
-    solver.setObjectiveCoefficient(x3, 4);
-    solver.setMaximization();
+    solver.objective().setCoefficient(x1, 10);
+    solver.objective().setCoefficient(x2, 6);
+    solver.objective().setCoefficient(x3, 4);
+    solver.objective().setMaximization();
 
     // x1 + x2 + x3 <= 100.
     MPConstraint c0 = solver.makeConstraint(-infinity, 100.0);
@@ -93,7 +93,8 @@ public class LinearProgramming {
                        " milliseconds");
 
     // The objective value of the solution.
-    System.out.println("Optimal objective value = " + solver.objectiveValue());
+    System.out.println("Optimal objective value = " +
+                       solver.objective().value());
 
     // The value of each variable in the solution.
     System.out.println("x1 = " + x1.solutionValue());

examples/csharp/csintegerprogramming.cs

@@ -29,8 +29,8 @@ public class CsIntegerProgramming
     Variable x2 = solver.MakeIntVar(0.0, double.PositiveInfinity, "x2");
 
     // Minimize x1 + 2 * x2.
-    solver.SetObjectiveCoefficient(x1, 1);
-    solver.SetObjectiveCoefficient(x2, 2);
+    solver.Objective().SetCoefficient(x1, 1);
+    solver.Objective().SetCoefficient(x2, 2);
 
     // 2 * x2 + 3 * x1 >= 17.
     Constraint ct = solver.MakeConstraint(17, double.PositiveInfinity);
@@ -50,7 +50,8 @@ public class CsIntegerProgramming
                       " milliseconds");
 
     // The objective value of the solution.
-    Console.WriteLine("Optimal objective value = " + solver.ObjectiveValue());
+    Console.WriteLine("Optimal objective value = " +
+                      solver.Objective().Value());
 
     // The value of each variable in the solution.
     Console.WriteLine("x1 = " + x1.SolutionValue());
@@ -89,7 +90,8 @@ public class CsIntegerProgramming
                       " milliseconds");
 
     // The objective value of the solution.
-    Console.WriteLine("Optimal objective value = " + solver.ObjectiveValue());
+    Console.WriteLine("Optimal objective value = " +
+                      solver.Objective().Value());
 
     // The value of each variable in the solution.
     Console.WriteLine("x1 = " + x1.SolutionValue());

examples/csharp/cslinearprogramming.cs

@@ -30,10 +30,10 @@ public class CsLinearProgramming
     Variable x3 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x3");
 
     // Maximize 10 * x1 + 6 * x2 + 4 * x3.
-    solver.SetObjectiveCoefficient(x1, 10);
-    solver.SetObjectiveCoefficient(x2, 6);
-    solver.SetObjectiveCoefficient(x3, 4);
-    solver.SetMaximization();
+    solver.Objective().SetCoefficient(x1, 10);
+    solver.Objective().SetCoefficient(x2, 6);
+    solver.Objective().SetCoefficient(x3, 4);
+    solver.Objective().SetMaximization();
 
     // x1 + x2 + x3 <= 100.
     Constraint c0 = solver.MakeConstraint(double.NegativeInfinity, 100.0);
@@ -68,7 +68,8 @@ public class CsLinearProgramming
                       " milliseconds");
 
     // The objective value of the solution.
-    Console.WriteLine("Optimal objective value = " + solver.ObjectiveValue());
+    Console.WriteLine("Optimal objective value = " +
+                      solver.Objective().Value());
 
     // The value of each variable in the solution.
     Console.WriteLine("x1 = " + x1.SolutionValue());
@@ -122,7 +123,8 @@ public class CsLinearProgramming
                       " milliseconds");
 
     // The objective value of the solution.
-    Console.WriteLine("Optimal objective value = " + solver.ObjectiveValue());
+    Console.WriteLine("Optimal objective value = " +
+                      solver.Objective().Value());
 
     // The value of each variable in the solution.
     Console.WriteLine("x1 = " + x1.SolutionValue());

examples/csharp/volsay.cs

@@ -57,7 +57,7 @@ public class Volsay
       return;
     }
 
-    Console.WriteLine("Objective: {0}", solver.ObjectiveValue());
+    Console.WriteLine("Objective: {0}", solver.Objective().Value());
 
     Console.WriteLine("Gas      : {0} ReducedCost: {1}",
                       Gas.SolutionValue(),

examples/csharp/volsay3.cs

@@ -87,7 +87,7 @@ public class Volsay3
       return;
     }
 
-    Console.WriteLine("Objective: {0}", solver.ObjectiveValue());
+    Console.WriteLine("Objective: {0}", solver.Objective().Value());
     foreach(int p in PRODUCTS) {
       Console.WriteLine("{0,-10}: {1} ReducedCost: {2}",
                         products[p],

examples/python/3_jugs_mip.py

@@ -150,7 +150,7 @@ def main(sol = 'GLPK'):
   solver.Solve()
 
   print
-  print 'z: ', int(solver.ObjectiveValue())
+  print 'z: ', int(solver.Objective().Value())
 
   t = start
   while t != end:

examples/python/assignment6_mip.py

@@ -136,7 +136,7 @@ def main(sol = 'GLPK'):
   solver.Solve()
 
   print
-  print 'z: ', int(solver.ObjectiveValue())
+  print 'z: ', int(solver.Objective().Value())
 
   print 'Assigned'
   for j in J:

examples/python/blending.py

@@ -106,7 +106,7 @@ def main(sol = 'GLPK'):
 
   print
 
-  print 'z = ', solver.ObjectiveValue()
+  print 'z = ', solver.Objective().Value()
   print 'Metals'
   for i in Metals:
     print p[i].SolutionValue(),

examples/python/coloring_ip.py

@@ -143,7 +143,7 @@ def main(sol = 'GLPK'):
   solver.Solve()
 
   print
-  print "number of colors:", int(solver.ObjectiveValue())
+  print "number of colors:", int(solver.Objective().Value())
   print "colors used:", [int(u[i].SolutionValue()) for i in range(nc)]
   print
 

examples/python/diet1_mip.py

@@ -94,7 +94,7 @@ def main(sol = 'GLPK'):
   #
   solver.Solve()
 
-  print "Cost:", solver.ObjectiveValue()
+  print "Cost:", solver.Objective().Value()
   print [int(x[i].SolutionValue()) for i in range(n)]
 
   print

examples/python/game_theory_taha.py

@@ -74,7 +74,7 @@ def main(sol = 'GLPK'):
 
   print
   print 'row player:';
-  print 'v = ', solver.ObjectiveValue()
+  print 'v = ', solver.Objective().Value()
   print 'Strategies: '
   for i in range(rows):
     print x1[i].SolutionValue(),
@@ -101,7 +101,7 @@ def main(sol = 'GLPK'):
 
   print
   print 'column player:';
-  print 'v2 = ', solver.ObjectiveValue()
+  print 'v2 = ', solver.Objective().Value()
   print 'Strategies: '
   for i in range(rows):
     print x2[i].SolutionValue(),

examples/python/integer_programming.py

@@ -45,8 +45,9 @@ def RunIntegerExampleCppStyleAPI(optimization_problem_type):
   x2 = solver.IntVar(0.0, infinity, 'x2')
 
   # Minimize x1 + 2 * x2.
-  solver.SetObjectiveCoefficient(x1, 1)
-  solver.SetObjectiveCoefficient(x2, 2)
+  objective = solver.Objective()
+  objective.SetCoefficient(x1, 1)
+  objective.SetCoefficient(x2, 2)
 
   # 2 * x2 + 3 * x1 >= 17.
   ct = solver.Constraint(17, infinity)
@@ -69,7 +70,7 @@ def SolveAndPrint(solver, variable_list):
   print('Problem solved in %f milliseconds' % solver.WallTime())
 
   # The objective value of the solution.
-  print('Optimal objective value = %f' % solver.ObjectiveValue())
+  print('Optimal objective value = %f' % solver.Objective().Value())
 
   # The value of each variable in the solution.
   for variable in variable_list:

examples/python/knapsack_mip.py

@@ -86,7 +86,7 @@ def main(sol = 'GLPK'):
   solver.Solve()
 
   print
-  print 'z: ', int(solver.ObjectiveValue())
+  print 'z: ', int(solver.Objective().Value())
 
   print 'take:',
   for i in items:

examples/python/least_square.py

@@ -81,7 +81,7 @@ def main(sol = 'GLPK'):
   solver.Solve()
 
   print
-  print 'z = ', solver.ObjectiveValue()
+  print 'z = ', solver.Objective().Value()
   for i in range(p + 1):
     print a[i].SolutionValue(),
   print

examples/python/linear_programming.py

@@ -50,10 +50,11 @@ def RunLinearExampleCppStyleAPI(optimization_problem_type):
   x3 = solver.NumVar(0.0, infinity, 'x3')
 
   # Maximize 10 * x1 + 6 * x2 + 4 * x3.
-  solver.SetObjectiveCoefficient(x1, 10)
-  solver.SetObjectiveCoefficient(x2, 6)
-  solver.SetObjectiveCoefficient(x3, 4)
-  solver.SetMaximization()
+  objective = solver.Objective()
+  objective.SetCoefficient(x1, 10)
+  objective.SetCoefficient(x2, 6)
+  objective.SetCoefficient(x3, 4)
+  objective.SetMaximization()
 
   # x1 + x2 + x3 <= 100.
   c0 = solver.Constraint(-infinity, 100.0, 'c0')
@@ -89,7 +90,7 @@ def SolveAndPrint(solver, variable_list, constraint_list):
   print('Problem solved in %f milliseconds' % solver.WallTime())
 
   # The objective value of the solution.
-  print('Optimal objective value = %f' % solver.ObjectiveValue())
+  print('Optimal objective value = %f' % solver.Objective().Value())
 
   # The value of each variable in the solution.
   for variable in variable_list:

examples/python/production.py

@@ -86,7 +86,7 @@ def main(sol = 'GLPK'):
   solver.Solve()
 
   print
-  print 'z = ', solver.ObjectiveValue()
+  print 'z = ', solver.Objective().Value()
 
   for p in range(num_products):
      print products[p], ': inside:', inside[p].SolutionValue(), '(ReducedCost:', inside[p].ReducedCost(), ')',

examples/python/stigler.py

@@ -365,7 +365,7 @@ def main(sol = 'GLPK'):
 
   print
 
-  print 'Cost = %0.2f' % solver.ObjectiveValue()
+  print 'Cost = %0.2f' % solver.Objective().Value()
   # print 'Cost:', cost.SolutionValue()
   print 'Total cost: %0.2f' % total_cost.SolutionValue()
   print

examples/python/volsay.py

@@ -62,7 +62,7 @@ def main(unused_argv):
   solver.Solve()
 
   print
-  print 'objective = ', solver.ObjectiveValue()
+  print 'objective = ', solver.Objective().Value()
   print 'Gas = ', Gas.SolutionValue(), 'ReducedCost =', Gas.ReducedCost()
   print 'Chloride:', Chloride.SolutionValue(), 'ReducedCost =', Chloride.ReducedCost()
 

examples/python/volsay2.py

@@ -67,7 +67,7 @@ def main(unused_argv):
   solver.Solve()
 
   print
-  print 'objective = ', solver.ObjectiveValue()
+  print 'objective = ', solver.Objective().Value()
   for i in range(num_products):
       print products[i], '=', production[i].SolutionValue(),
       print 'ReducedCost = ', production[i].ReducedCost()

examples/python/volsay3.py

@@ -76,7 +76,7 @@ def main(unused_argv):
   solver.Solve()
 
   print
-  print 'objective = ', solver.ObjectiveValue()
+  print 'objective = ', solver.Objective().Value()
   for i in range(num_products):
       print products[i], '=', production[i].SolutionValue(),
       print 'ReducedCost = ', production[i].ReducedCost()

src/linear_solver/gurobi_interface.cc

@@ -664,9 +664,8 @@ MPSolver::ResultStatus GurobiInterface::Solve(const MPSolverParameters& param) {
     }
   }
 
-  if (solution_count > 0) {
-    DCHECK(result_status_ == MPSolver::FEASIBLE ||
-           result_status_ == MPSolver::OPTIMAL);
+  if (solution_count > 0 && (result_status_ == MPSolver::FEASIBLE ||
+                             result_status_ == MPSolver::OPTIMAL)) {
     // Get the results.
     const int total_num_rows = solver_->constraints_.size();
     const int total_num_cols = solver_->variables_.size();

src/linear_solver/linear_solver.cc

@@ -263,37 +263,6 @@ void MPVariable::SetInteger(bool integer) {
   }
 }
 
-// ----- Objective (DEPRECATED methods) -----
-
-double MPSolver::objective_value() const { return Objective().Value(); }
-
-double MPSolver::best_objective_bound() const {
-  return Objective().BestBound();
-}
-
-void MPSolver::ClearObjective() { MutableObjective()->Clear(); }
-
-void MPSolver::SetObjectiveCoefficient(const MPVariable* const var,
-                                       double coeff) {
-  MutableObjective()->SetCoefficient(var, coeff);
-}
-
-void MPSolver::SetObjectiveOffset(double value) {
-  MutableObjective()->SetOffset(value);
-}
-
-void MPSolver::AddObjectiveOffset(double value) {
-  MutableObjective()->AddOffset(value);
-}
-
-void MPSolver::SetOptimizationDirection(bool maximize) {
-  MutableObjective()->SetOptimizationDirection(maximize);
-}
-
-bool MPSolver::Maximization() const { return Objective().maximization(); }
-
-bool MPSolver::Minimization() const { return Objective().minimization(); }
-
 // ----- Version -----
 
 std::string MPSolver::SolverVersion() const { return interface_->SolverVersion(); }
@@ -506,9 +475,9 @@ MPSolver::LoadStatus MPSolver::LoadModelFromProto(
                          ct_proto.coefficient(j));
     }
   }
-  SetOptimizationDirection(input_model.maximize());
+  objective->SetOptimizationDirection(input_model.maximize());
   if (input_model.has_objective_offset()) {
-    MutableObjective()->SetOffset(input_model.objective_offset());
+    objective->SetOffset(input_model.objective_offset());
   }
   return MPSolver::NO_ERROR;
 }
@@ -1426,3 +1395,4 @@ int MPSolverParameters::GetIntegerParam(MPSolverParameters::IntegerParam param)
 
 
 }  // namespace operations_research
+

src/linear_solver/linear_solver.h

@@ -517,22 +517,6 @@ class MPSolver {
   // Debugging: verify that the given MPVariable* belongs to this solver.
   bool OwnsVariable(const MPVariable* var) const;
 
-  // *** DEPRECATED ***
-  // Setters and getters for the objective. Please call
-  // Objective().Getter() and MutableObjective()->Setter() instead.
-  // TODO(user): remove when they are no longer used.
-  double objective_value() const;
-  double best_objective_bound() const;
-  void ClearObjective();
-  void SetObjectiveCoefficient(const MPVariable* const var, double coeff);
-  void SetObjectiveOffset(double value);
-  void AddObjectiveOffset(double value);
-  void SetOptimizationDirection(bool maximize);
-  void SetMinimization() { SetOptimizationDirection(false); }
-  void SetMaximization() { SetOptimizationDirection(true); }
-  bool Maximization() const;
-  bool Minimization() const;
-
  private:
   // Computes the size of the constraint with the largest number of
   // coefficients with index in [min_constraint_index,

src/linear_solver/linear_solver.swig

@@ -24,7 +24,6 @@
 %}
 
 #ifdef SWIGPYTHON
-
 // Define the renaming of methods.
 %ignore MakeBoolVarArray;
 %ignore MakeIntVarArray;
@@ -47,7 +46,6 @@
 %rename (LookupVariable) LookupVariableOrNull;
 %rename (Nodes) nodes;
 %rename (NumVar) MakeNumVar;
-%rename (ObjectiveValue) objective_value;
 %rename (Offset) offset;
 %rename (ReducedCost) reduced_cost;
 %rename (SetLb) SetLB;
@@ -437,30 +435,30 @@ class LinearConstraint(object):
       return self.Constraint(*args)
 
     def Minimize(self, expr):
-      self.ClearObjective()
-      self.SetMinimization()
+      self.Objective().Clear()
+      self.Objective().SetMinimization()
       coeffs = {}
       offset = expr.Visit(coeffs)
-      self.AddObjectiveOffset(offset)
+      self.Objective().SetOffset(offset)
       if sys.version_info[0] >= 3: # Python 3
         for v, c, in coeffs.items():
-          self.SetObjectiveCoefficient(v, float(c))
+          self.Objective().SetCoefficient(v, float(c))
       else:
         for v, c, in coeffs.iteritems():
-          self.SetObjectiveCoefficient(v, float(c))
+          self.Objective().SetCoefficient(v, float(c))
 
     def Maximize(self, expr):
-      self.ClearObjective()
-      self.SetMaximization()
+      self.Objective().Clear()
+      self.Objective().SetMaximization()
       coeffs = {}
       offset = expr.Visit(coeffs)
-      self.AddObjectiveOffset(offset)
+      self.Objective().SetOffset(offset)
       if sys.version_info[0] >= 3: # Python 3
         for v, c, in coeffs.items():
-          self.SetObjectiveCoefficient(v, float(c))
+          self.Objective().SetCoefficient(v, float(c))
       else:
         for v, c, in coeffs.iteritems():
-          self.SetObjectiveCoefficient(v, float(c))
+          self.Objective().SetCoefficient(v, float(c))
   }
 }
 
@@ -520,12 +518,11 @@ namespace operations_research {
 %rename (setIntegerParam) MPSolverParameters::SetIntegerParam;
 
 // Rename rules on MPSolver.
-%rename (addObjectiveOffset) MPSolver::AddObjectiveOffset;
-%rename (bestObjectiveBound) MPSolver::best_objective_bound;
 %rename (checkAllNamesValidity) MPSolver::CheckAllNamesValidity;
 %rename (checkNameValidity) MPSolver::CheckNameValidity;
+%rename (clear) MPConstraint::Clear;
+%rename (clear) MPObjective::Clear;
 %rename (clear) MPSolver::Clear;
-%rename (clearObjective) MPSolver::ClearObjective;
 %rename (computeExactConditionNumber) MPSolver::ComputeExactConditionNumber;
 %rename (loadModel) MPSolver::LoadModel;
 %rename (lookupVariableOrNull) MPSolver::LookupVariableOrNull;
@@ -539,13 +536,12 @@ namespace operations_research {
 %rename (numConstraints) MPSolver::NumConstraints;
 %rename (numVariables) MPSolver::NumVariables;
 %rename (objective) MPSolver::MutableObjective;
-%rename (objectiveValue) MPSolver::objective_value;
 %rename (reset) MPSolver::Reset;
-%rename (setMaximization) MPSolver::SetMaximization;
-%rename (setMinimization) MPSolver::SetMinimization;
-%rename (setObjectiveCoefficient) MPSolver::SetObjectiveCoefficient;
-%rename (setObjectiveOffset) MPSolver::SetObjectiveOffset;
-%rename (setOptimizationDirection) MPSolver::SetOptimizationDirection;
+%rename (setMaximization) MPObjective::SetMaximization();
+%rename (setMinimization) MPObjective::SetMinimization();
+%rename (setCoefficient) MPObjective::SetCoefficient;
+%rename (setOffset) MPObjective::SetOffset;
+%rename (setOptimizationDirection) MPObjective::SetOptimizationDirection;
 %rename (setTimeLimit) MPSolver::set_time_limit;
 %rename (setWriteModelFilename) MPSolver::set_write_model_filename;
 %rename (solve) MPSolver::Solve;
@@ -679,6 +675,9 @@ namespace operations_research {
 %ignore MPSolver::ExportModelToNewProto;
 %ignore MPSolver::FillSolutionResponse;
 %ignore MPSolver::SolveWithProtocolBuffers;
+// Ignore Objective(), use MutableObjective() instead.
+%ignore MPSolver::Objective;
+%rename (Objective) MPSolver::MutableObjective;
 
 %typemap(cscode) MPVariable %{
   public static LinearExpr operator+(Variable a, double v)
@@ -1040,44 +1039,44 @@ namespace operations_research {
 
   public void Minimize(LinearExpr expr)
   {
-    ClearObjective();
-    SetMinimization();
+    Objective().Clear();
+    Objective().SetMinimization();
     Dictionary<Variable, double> coefficients =
         new Dictionary<Variable, double>();
     double constant = expr.Visit(coefficients);
     foreach (KeyValuePair<Variable, double> pair in coefficients)
     {
-      SetObjectiveCoefficient(pair.Key, pair.Value);
+      Objective().SetCoefficient(pair.Key, pair.Value);
     }
-    SetObjectiveOffset(constant);
+    Objective().SetOffset(constant);
   }
 
   public void Maximize(LinearExpr expr)
   {
-    ClearObjective();
-    SetMaximization();
+    Objective().Clear();
+    Objective().SetMaximization();
     Dictionary<Variable, double> coefficients =
         new Dictionary<Variable, double>();
     double constant = expr.Visit(coefficients);
     foreach (KeyValuePair<Variable, double> pair in coefficients)
     {
-      SetObjectiveCoefficient(pair.Key, pair.Value);
+      Objective().SetCoefficient(pair.Key, pair.Value);
     }
-    SetObjectiveOffset(constant);
+    Objective().SetOffset(constant);
   }
 
   public void Minimize(Variable var)
   {
-    ClearObjective();
-    SetMinimization();
-    SetObjectiveCoefficient(var, 1.0);
+    Objective().Clear();
+    Objective().SetMinimization();
+    Objective().SetCoefficient(var, 1.0);
   }
 
   public void Maximize(Variable var)
   {
-    ClearObjective();
-    SetMaximization();
-    SetObjectiveCoefficient(var, 1.0);
+    Objective().Clear();
+    Objective().SetMaximization();
+    Objective().SetCoefficient(var, 1.0);
   }
 %}
 

src/linear_solver/model_exporter.cc

@@ -15,6 +15,7 @@
 #include <cmath>
 #include <limits>
 
+#include "base/commandlineflags.h"
 #include "base/integral_types.h"
 #include "base/logging.h"
 #include "base/stringprintf.h"
@@ -24,6 +25,10 @@
 #include "linear_solver/linear_solver2.pb.h"
 #include "util/fp_utils.h"
 
+DEFINE_bool(lp_shows_unused_variables, false,
+            "Decides wether variable unused in the objective and constraints"
+            " are shown when exported to a file using the lp format.");
+
 namespace operations_research {
 
 using new_proto::MPConstraintProto;
@@ -111,6 +116,9 @@ void MPModelProtoExporter::AppendComments(const std::string& separator,
                 num_integer_variables_);
   StringAppendF(output, "%s     %-14s : %d\n", sep, "Continuous",
                 num_continuous_variables_);
+  if (FLAGS_lp_shows_unused_variables) {
+    StringAppendF(output, "%s Unused variables are shown\n", sep);
+  }
 }
 
 bool MPModelProtoExporter::AppendLpTerm(int var_index, double coefficient,
@@ -189,22 +197,28 @@ bool MPModelProtoExporter::ExportModelAsLpFormat(bool obfuscated,
   if (proto_.objective_offset() != 0.0) {
     StringAppendF(output, "%-+.16G Constant ", proto_.objective_offset());
   }
-  for (int i = 0; i < proto_.variable_size(); ++i) {
-    if (!AppendLpTerm(i, proto_.variable(i).objective_coefficient(), output)) {
+  std::vector<bool> show_variable(proto_.variable_size(),
+                             FLAGS_lp_shows_unused_variables);
+  for (int var_index = 0; var_index < proto_.variable_size(); ++var_index) {
+    const double coeff = proto_.variable(var_index).objective_coefficient();
+    if (!AppendLpTerm(var_index, coeff, output)) {
       return false;
     }
+    show_variable[var_index] = coeff != 0.0 || FLAGS_lp_shows_unused_variables;
   }
-
   // Constraints
   StringAppendF(output, "\nSubject to\n");
   for (int cst_index = 0; cst_index < proto_.constraint_size(); ++cst_index) {
     const MPConstraintProto& ct_proto = proto_.constraint(cst_index);
     std::string term;
     for (int i = 0; i < ct_proto.var_index_size(); ++i) {
-      if (!AppendLpTerm(ct_proto.var_index(i), ct_proto.coefficient(i),
-                        &term)) {
+      const int var_index = ct_proto.var_index(i);
+      const double coeff = ct_proto.coefficient(i);
+      if (!AppendLpTerm(var_index, coeff, &term)) {
         return false;
       }
+      show_variable[var_index] =
+          coeff != 0.0 || FLAGS_lp_shows_unused_variables;
     }
     const double lb = ct_proto.lower_bound();
     const double ub = ct_proto.upper_bound();
@@ -238,6 +252,7 @@ bool MPModelProtoExporter::ExportModelAsLpFormat(bool obfuscated,
     StringAppendF(output, " 1 <= Constant <= 1\n");
   }
   for (int var_index = 0; var_index < proto_.variable_size(); ++var_index) {
+    if (!show_variable[var_index]) continue;
     const MPVariableProto& var_proto = proto_.variable(var_index);
     const double lb = var_proto.lower_bound();
     const double ub = var_proto.upper_bound();
@@ -260,6 +275,7 @@ bool MPModelProtoExporter::ExportModelAsLpFormat(bool obfuscated,
   if (num_binary_variables_ > 0) {
     StringAppendF(output, "Binaries\n");
     for (int var_index = 0; var_index < proto_.variable_size(); ++var_index) {
+      if (!show_variable[var_index]) continue;
       const MPVariableProto& var_proto = proto_.variable(var_index);
       if (IsBoolean(var_proto)) {
         StringAppendF(output, " %s\n", GetVariableName(var_index).c_str());
@@ -271,6 +287,7 @@ bool MPModelProtoExporter::ExportModelAsLpFormat(bool obfuscated,
   if (num_integer_variables_ > 0) {
     StringAppendF(output, "Generals\n");
     for (int var_index = 0; var_index < proto_.variable_size(); ++var_index) {
+      if (!show_variable[var_index]) continue;
       const MPVariableProto& var_proto = proto_.variable(var_index);
       if (var_proto.is_integer() && !IsBoolean(var_proto)) {
         StringAppendF(output, " %s\n", GetVariableName(var_index).c_str());

src/linear_solver/model_exporter.h

@@ -116,6 +116,11 @@ class MPModelProtoExporter {
 
   // Appends a general "Comment" section with useful metadata about the model
   // to "output".
+  // Note(user): there may be less variables in output than in the original
+  // model, as unused variables are not shown by default. Similarly, there
+  // may be more constraints in a .lp file as in the original model as
+  // a constraint lhs <= term <= rhs will be output as the two constraints
+  // term >= lhs and term <= rhs.
   void AppendComments(const std::string& separator, std::string* output) const;
 
   // Appends a term to "output", in "Lp" format.