Add support for quadratic programming to the barrier method

cpp/include/cuopt/linear_programming/optimization_problem.hpp

@@ -196,6 +196,45 @@ class optimization_problem_t {
    * @param objective_offset Objective offset value.
    */
   void set_objective_offset(f_t objective_offset);
+
+  /**
+   * @brief Set the quadratic objective matrix (Q) in CSR format for QPS files.
+   *
+   * @note This is used for quadratic programming problems where the objective
+   * function contains quadratic terms: (1/2) * x^T * Q * x + c^T * x
+   *
+   * @param[in] Q_offsets Offsets of the CSR representation of the quadratic objective matrix
+   * @param size_offsets Size of the Q_offsets array
+   * @param[in] Q_indices Indices of the CSR representation of the quadratic objective matrix
+   * @param size_indices Size of the Q_indices array
+   * @param[in] Q_values Values of the CSR representation of the quadratic objective matrix
+   * @param size_values Size of the Q_values array
+   */
+  void set_quadratic_objective_matrix(const i_t* Q_offsets,
+                                      i_t size_offsets,
+                                      const i_t* Q_indices,
+                                      i_t size_indices,
+                                      const f_t* Q_values,
+                                      i_t size_values);
+
+  /**
+   * @brief Get the quadratic objective matrix offsets
+   * @return const reference to the Q_offsets vector
+   */
+  const std::vector<i_t>& get_quadratic_objective_offsets() const;
+
+  /**
+   * @brief Get the quadratic objective matrix indices
+   * @return const reference to the Q_indices vector
+   */
+  const std::vector<i_t>& get_quadratic_objective_indices() const;
+
+  /**
+   * @brief Get the quadratic objective matrix values
+   * @return const reference to the Q_values vector
+   */
+  const std::vector<f_t>& get_quadratic_objective_values() const;
+
   /**
    * @brief Set the variables (x) lower bounds.
    * @note Setting before calling the solver is optional, default value for all
@@ -392,6 +431,12 @@ class optimization_problem_t {
   f_t objective_scaling_factor_{1};
   /** offset of the objective function */
   f_t objective_offset_{0};
+
+  /** Quadratic objective matrix in CSR format (for (1/2) * x^T * Q * x term) */
+  std::vector<i_t> Q_offsets_;
+  std::vector<i_t> Q_indices_;
+  std::vector<f_t> Q_values_;
+
   /** lower bounds of the variables (primal part) */
   rmm::device_uvector<f_t> variable_lower_bounds_;
   /** upper bounds of the variables (primal part) */

cpp/libmps_parser/src/mps_parser.cpp

@@ -506,6 +506,7 @@ void mps_parser_t<i_t, f_t>::fill_problem(mps_data_model_t<i_t, f_t>& problem)
 
   // Process QUADOBJ data if present (upper triangular format)
   if (!quadobj_entries.empty()) {
+    printf("Quadratic objective matrix: %zu nonzeros\n", quadobj_entries.size());
     // Convert quadratic objective entries to CSR format using double transpose
     // QUADOBJ stores upper triangular elements, so we expand to full symmetric matrix
     i_t num_vars    = static_cast<i_t>(var_names.size());