Implement tabu columns in column generation

include/columngenerationsolver/algorithms/column_generation.hpp

@@ -2,6 +2,8 @@
 
 #include "columngenerationsolver/linear_programming_solver.hpp"
 
+#include <unordered_set>
+
 namespace columngenerationsolver
 {
 
@@ -85,6 +87,15 @@ struct ColumnGenerationParameters: Parameters
     bool automatic_directional_smoothing = false;
 
 
+    /**
+     * Tabu columns.
+     *
+     * These columns are never added to the LP solver and therefore won't be
+     * part of the returned solution.
+     */
+    std::unordered_set<std::shared_ptr<const Column>>* tabu = nullptr;
+
+
     virtual int format_width() const override { return 41; }
 
     virtual void format(std::ostream& os) const override

src/algorithms/column_generation.cpp

@@ -300,6 +300,11 @@ const ColumnGenerationOutput columngenerationsolver::column_generation(
                     != infeasible_columns.end())
                 continue;
 
+            // Don't add a tabu column.
+            if (parameters.tabu != nullptr
+                    && parameters.tabu->find(column) != parameters.tabu->end())
+                continue;
+
             std::vector<RowIdx> row_ids;
             std::vector<Value> row_coefficients;
             bool ok = true;
@@ -403,6 +408,11 @@ const ColumnGenerationOutput columngenerationsolver::column_generation(
                 if (solver_generated_columns.find(column) != solver_generated_columns.end())
                     continue;
 
+                // Don't add a tabu column.
+                if (parameters.tabu != nullptr
+                        && parameters.tabu->find(column) != parameters.tabu->end())
+                    continue;
+
                 // Add the column if its reduced cost is negative.
                 Value rc = compute_reduced_cost(*column, duals_out);
                 if (model.objective_sense == optimizationtools::ObjectiveDirection::Minimize
@@ -626,12 +636,12 @@ const ColumnGenerationOutput columngenerationsolver::column_generation(
                     // Look for negative reduced cost columns.
                     for (const std::shared_ptr<const Column>& column: all_columns) {
 
-                      // Discard columns which have already been generated.
-                      // If they were worth adding to the LP, then they would
-                      // have been added at the previous step (looking for
-                      // column from the pool).
-                      if (column_pool.find(column) != column_pool.end())
-                          continue;
+                        // Discard columns which have already been generated.
+                        // If they were worth adding to the LP, then they would
+                        // have been added at the previous step (looking for
+                        // column from the pool).
+                        if (column_pool.find(column) != column_pool.end())
+                            continue;
 
                         // Store these new columns.
                         column_pool.insert(column);
@@ -738,6 +748,7 @@ const ColumnGenerationOutput columngenerationsolver::column_generation(
 
             // Add new columns to the linear program.
             for (const std::shared_ptr<const Column>& column: new_columns) {
+
                 //std::cout << column << std::endl;
                 std::vector<RowIdx> ri;
                 std::vector<Value> rc;

src/algorithms/limited_discrepancy_search.cpp

@@ -2,7 +2,6 @@
 
 #include "columngenerationsolver/algorithm_formatter.hpp"
 
-#include <unordered_set>
 #include <set>
 
 using namespace columngenerationsolver;
@@ -143,7 +142,8 @@ const LimitedDiscrepancySearchOutput columngenerationsolver::limited_discrepancy
         }
 
         if (node->parent != nullptr
-                && node->value <= node->value_frac) {
+                && node->value <= node->value_frac
+                && !node->tabu) {
 
             node->relaxation_solution = node->parent->relaxation_solution;
 
@@ -192,6 +192,7 @@ const LimitedDiscrepancySearchOutput columngenerationsolver::limited_discrepancy
             }
             column_generation_parameters.column_pool = column_pool;
             column_generation_parameters.fixed_columns = fixed_columns.columns();
+            column_generation_parameters.tabu = &tabu;
 
             // Solve.
             auto cg_output = column_generation(