Fix: handle MPS OBJSENSE MAXIMIZE in reader (#93)

* Fix: handle MPS OBJSENSE MAXIMIZE in reader

* Fix: support inline OBJSENSE section declaration in MPS reader

* Style: clang-format continuation indent

* Handle objective sense (max/min) consistently across solver, API, and MPS reader

Keep problems in their original sense and normalize max→min once inside the core, reporting results back in the caller's sense (replaces the scattered
sign-flipping that caused objective/dual-sign bugs).

* apply clang format

* Fix: make objective_sense optional in create_lp_problem and repair test build

* Fix: free reduced_cost in cupdlpx_result_free

---------

Co-authored-by: Zedong Peng <peng_zedong@126.com>

Author: LucasBoTang

docs/C_API.md

@@ -15,7 +15,8 @@ lp_problem_t *create_lp_problem(
     const double *con_ub,                // constraint upper bounds (length m)
     const double *var_lb,                // variable lower bounds (length n)
     const double *var_ub,                // variable upper bounds (length n)
-    const double *objective_constant     // scalar objective offset
+    const double *objective_constant,    // scalar objective offset
+    const objective_sense_t *objective_sense // objective sense (NULL → minimize)
 );
 
 cupdlpx_result_t* solve_lp_problem(
@@ -32,6 +33,7 @@ cupdlpx_result_t* solve_lp_problem(
 - `var_lb`: Variable lower bounds. If `NULL`, defaults to all `-INFINITY`.
 - `var_ub`: Variable upper bounds. If `NULL`, defaults to all `+INFINITY`.
 - `objective_constant`: Scalar constant term added to the objective value. If `NULL`, defaults to `0.0`.
+- `objective_sense`: Objective sense, `OBJECTIVE_SENSE_MINIMIZE` or `OBJECTIVE_SENSE_MAXIMIZE`. If `NULL`, defaults to minimize.
 
 
 `solve_lp_problem` parameters:
@@ -70,7 +72,7 @@ int main() {
 
     // Build the problem
     lp_problem_t* prob = create_lp_problem(
-        c, &A_desc, l, u, NULL, NULL, NULL);
+        c, &A_desc, l, u, NULL, NULL, NULL, NULL);
 
     // Solve (NULL → use default parameters)
     cupdlpx_result_t* res = solve_lp_problem(prob, NULL);

include/cupdlpx.h

@@ -30,7 +30,8 @@ extern "C"
                                     const double *con_ub,
                                     const double *var_lb,
                                     const double *var_ub,
-                                    const double *objective_constant);
+                                    const double *objective_constant,
+                                    const objective_sense_t *objective_sense);
 
     // Set up initial primal and dual solution for an lp_problem_t
     void set_start_values(lp_problem_t *prob, const double *primal, const double *dual);

include/cupdlpx_types.h

@@ -43,6 +43,12 @@ extern "C"
         NORM_TYPE_L_INF = 1
     } norm_type_t;
 
+    typedef enum
+    {
+        OBJECTIVE_SENSE_MINIMIZE = 0,
+        OBJECTIVE_SENSE_MAXIMIZE = 1
+    } objective_sense_t;
+
     typedef struct
     {
         int num_variables;
@@ -51,6 +57,7 @@ extern "C"
         double *variable_upper_bound;
         double *objective_vector;
         double objective_constant;
+        objective_sense_t objective_sense;
 
         int *constraint_matrix_row_pointers;
         int *constraint_matrix_col_indices;

internal/internal_types.h

@@ -45,6 +45,7 @@ typedef struct
     double *variable_upper_bound;
     double *objective_vector;
     double objective_constant;
+    double original_objective_sign;
     cu_sparse_matrix_csr_t *constraint_matrix;
     cu_sparse_matrix_csr_t *constraint_matrix_t;
     double *constraint_lower_bound;

internal/solver.h

@@ -23,7 +23,7 @@ extern "C"
 {
 #endif
 
-    cupdlpx_result_t *optimize(const pdhg_parameters_t *params, lp_problem_t *original_problem);
+    cupdlpx_result_t *optimize(const pdhg_parameters_t *params, const lp_problem_t *original_problem);
 
 #ifdef __cplusplus
 }

internal/utils.h

@@ -125,7 +125,15 @@ extern "C"
 
     void check_termination_criteria(pdhg_solver_state_t *solver_state, const termination_criteria_t *criteria);
 
-    void print_initial_info(const pdhg_parameters_t *params, lp_problem_t *problem);
+    void print_initial_info(const pdhg_parameters_t *params, const lp_problem_t *problem);
+
+    void filter_constraint_matrix_entries(lp_problem_t *out, const lp_problem_t *in, const pdhg_parameters_t *params);
+
+    lp_problem_t preprocess_problem(const lp_problem_t *original, const pdhg_parameters_t *params);
+
+    void free_preprocessed_problem(const lp_problem_t *preprocessed, const lp_problem_t *original);
+
+    void restore_original_objective_sense(cupdlpx_result_t *result, objective_sense_t sense);
 
     void pdhg_final_log(const cupdlpx_result_t *result, const pdhg_parameters_t *params);
 

python/cupdlpx/model.py

@@ -355,23 +355,20 @@ def optimize(self):
         # check model sense
         if self.ModelSense not in (PDLP.MINIMIZE, PDLP.MAXIMIZE):
             raise ValueError("model_sense must be PDLP.MINIMIZE or PDLP.MAXIMIZE")
-        # determine sign
-        sign = 1 if self.ModelSense == PDLP.MINIMIZE else -1
-        # effective objective based on sense
-        c_eff  = sign * self.c if self.c is not None else None
-        c0_eff = sign * self.c0 if self.c0 is not None else None
+        minimize = self.ModelSense == PDLP.MINIMIZE
         # call the core solver
         info = solve_once(
             self.A,
-            c_eff,
-            c0_eff,
+            self.c,
+            self.c0,
             self.lb,
             self.ub,
             self.constr_lb,
             self.constr_ub,
             params=self._params,
             primal_start=self._primal_start,
-            dual_start=self._dual_start
+            dual_start=self._dual_start,
+            minimize=minimize,
         )
         # solutions
         self._x = np.asarray(info.get("X")) if info.get("X") is not None else None
@@ -380,8 +377,8 @@ def optimize(self):
         # objectives & gaps
         primal_obj_eff = info.get("PrimalObj")
         dual_obj_eff   = info.get("DualObj")
-        self._objval = sign * primal_obj_eff if primal_obj_eff is not None else None
-        self._dualobj = sign * dual_obj_eff if dual_obj_eff is not None else None
+        self._objval = primal_obj_eff if primal_obj_eff is not None else None
+        self._dualobj = dual_obj_eff if dual_obj_eff is not None else None
         self._gap = info.get("ObjectiveGap")
         self._rel_gap = info.get("RelativeObjectiveGap")
         # status & counters
@@ -398,8 +395,8 @@ def optimize(self):
         self._max_d_ray = info.get("MaxDualRayInfeas")
         p_ray_lin_eff  = info.get("PrimalRayLinObj")
         d_ray_obj_eff  = info.get("DualRayObj")
-        self._p_ray_lin_obj = sign * p_ray_lin_eff if p_ray_lin_eff is not None else None
-        self._d_ray_obj = sign * d_ray_obj_eff if d_ray_obj_eff is not None else None
+        self._p_ray_lin_obj = p_ray_lin_eff if p_ray_lin_eff is not None else None
+        self._d_ray_obj = d_ray_obj_eff if d_ray_obj_eff is not None else None
 
     def _clear_solution_cache(self) -> None:
         """

python_bindings/_core_bindings.cpp

@@ -464,7 +464,8 @@ static py::dict solve_once(py::object A,
                            py::object constraint_upper_bound,    // u  (optional → inf)
                            py::object params = py::none(),       // PDHG parameters (optional → default)
                            py::object primal_start = py::none(), // warm start primal solution (optional)
-                           py::object dual_start = py::none()    // warm start dual solution (optional)
+                           py::object dual_start = py::none(),   // warm start dual solution (optional)
+                           bool minimize = true                  // objective sense (true → minimize)
 )
 {
     // parse matrix
@@ -492,13 +493,15 @@ static py::dict solve_once(py::object A,
     }
 
     // build problem
+    objective_sense_t sense = minimize ? OBJECTIVE_SENSE_MINIMIZE : OBJECTIVE_SENSE_MAXIMIZE;
     lp_problem_t *prob = create_lp_problem(c_ptr,      // objective vector
                                            &view.desc, // constraint matrix
                                            l_ptr,      // constraint lower bound
                                            u_ptr,      // constraint upper bound
                                            lb_ptr,     // variable lower bound
                                            ub_ptr,     // variable upper bound
-                                           c0_ptr      // objective constant
+                                           c0_ptr,     // objective constant
+                                           &sense      // objective sense
     );
     if (!prob)
     {
@@ -595,5 +598,6 @@ PYBIND11_MODULE(_cupdlpx_core, m)
           py::arg("constraint_upper_bound") = py::none(),
           py::arg("params") = py::none(),
           py::arg("primal_start") = py::none(),
-          py::arg("dual_start") = py::none());
+          py::arg("dual_start") = py::none(),
+          py::arg("minimize") = true);
 }

src/cupdlpx.c

@@ -29,7 +29,8 @@ lp_problem_t *create_lp_problem(const double *objective_c,
                                 const double *con_ub,
                                 const double *var_lb,
                                 const double *var_ub,
-                                const double *objective_constant)
+                                const double *objective_constant,
+                                const objective_sense_t *objective_sense)
 {
     lp_problem_t *prob = (lp_problem_t *)safe_malloc(sizeof(lp_problem_t));
     prob->primal_start = NULL;
@@ -105,6 +106,7 @@ lp_problem_t *create_lp_problem(const double *objective_c,
 
     // default fill values
     prob->objective_constant = objective_constant ? *objective_constant : 0.0;
+    prob->objective_sense = objective_sense ? *objective_sense : OBJECTIVE_SENSE_MINIMIZE;
     fill_or_copy(&prob->objective_vector, prob->num_variables, objective_c, 0.0);
     fill_or_copy(&prob->variable_lower_bound, prob->num_variables, var_lb, -INFINITY);
     fill_or_copy(&prob->variable_upper_bound, prob->num_variables, var_ub, INFINITY);
@@ -123,6 +125,7 @@ void cupdlpx_result_free(cupdlpx_result_t *results)
 
     free(results->primal_solution);
     free(results->dual_solution);
+    free(results->reduced_cost);
     free(results);
 }
 

src/mps_parser.c

@@ -326,7 +326,7 @@ typedef struct
     char *objective_row_name;
     char *current_col_name;
     double objective_constant;
-    bool is_maximize;
+    objective_sense_t objective_sense;
     int error_flag;
 
 } MpsParserState;
@@ -435,7 +435,7 @@ lp_problem_t *read_mps_file(const char *filename)
         if (n_tokens == 0)
             continue;
 
-        if (n_tokens == 1 && isalpha(tokens[0][0]))
+        if (isalpha((unsigned char)tokens[0][0]))
         {
             MpsSection next_section = SEC_NONE;
             if (strcmp(tokens[0], "ROWS") == 0)
@@ -448,32 +448,51 @@ lp_problem_t *read_mps_file(const char *filename)
                 next_section = SEC_RANGES;
             else if (strcmp(tokens[0], "BOUNDS") == 0)
                 next_section = SEC_BOUNDS;
-            else if (strcmp(tokens[0], "OBJSENSE") == 0)
+            else if (strcmp(tokens[0], "OBJSENSE") == 0 || strcmp(tokens[0], "OBJSENS") == 0)
                 next_section = SEC_OBJSENSE;
             else if (strcmp(tokens[0], "ENDATA") == 0)
             {
                 next_section = SEC_ENDATA;
             }
 
-            if (current_section == SEC_ROWS && next_section != SEC_ROWS && !rows_finalized)
+            bool inline_max = next_section == SEC_OBJSENSE && n_tokens >= 2 &&
+                (strcmp(tokens[1], "MAX") == 0 || strcmp(tokens[1], "MAXIMIZE") == 0);
+            bool inline_min = next_section == SEC_OBJSENSE && n_tokens >= 2 &&
+                (strcmp(tokens[1], "MIN") == 0 || strcmp(tokens[1], "MINIMIZE") == 0);
+            bool is_header = next_section != SEC_NONE && (n_tokens == 1 || inline_max || inline_min);
+
+            if (is_header)
             {
-                if (finalize_rows(&state) != 0)
-                    state.error_flag = 1;
-                rows_finalized = true;
-            }
+                if (current_section == SEC_ROWS && next_section != SEC_ROWS && !rows_finalized)
+                {
+                    if (finalize_rows(&state) != 0)
+                        state.error_flag = 1;
+                    rows_finalized = true;
+                }
 
-            current_section = next_section;
-            if (current_section == SEC_ENDATA)
-                break;
-            continue;
+                current_section = next_section;
+                if (current_section == SEC_ENDATA)
+                    break;
+
+                if (inline_max)
+                    state.objective_sense = OBJECTIVE_SENSE_MAXIMIZE;
+                else if (inline_min)
+                    state.objective_sense = OBJECTIVE_SENSE_MINIMIZE;
+
+                continue;
+            }
         }
 
         switch (current_section)
         {
             case SEC_OBJSENSE:
-                if (n_tokens > 0 && (strcmp(tokens[0], "MAX") == 0 || strcmp(tokens[0], "MAXIMIZE") == 0))
+                if (strcmp(tokens[0], "MAX") == 0 || strcmp(tokens[0], "MAXIMIZE") == 0)
+                {
+                    state.objective_sense = OBJECTIVE_SENSE_MAXIMIZE;
+                }
+                else if (strcmp(tokens[0], "MIN") == 0 || strcmp(tokens[0], "MINIMIZE") == 0)
                 {
-                    state.is_maximize = true;
+                    state.objective_sense = OBJECTIVE_SENSE_MINIMIZE;
                 }
                 break;
             case SEC_ROWS:
@@ -516,7 +535,8 @@ lp_problem_t *read_mps_file(const char *filename)
     prob->num_variables = state.col_map.size;
     prob->num_constraints = state.row_map.size;
     prob->constraint_matrix_num_nonzeros = state.coo_matrix.nnz;
-    prob->objective_constant = state.is_maximize ? -state.objective_constant : state.objective_constant;
+    prob->objective_constant = state.objective_constant;
+    prob->objective_sense = state.objective_sense;
 
     prob->objective_vector = state.objective_coeffs;
     prob->variable_lower_bound = state.var_lower_bounds;
@@ -533,14 +553,6 @@ lp_problem_t *read_mps_file(const char *filename)
     state.constraint_lower_bounds = NULL;
     state.constraint_upper_bounds = NULL;
 
-    if (state.is_maximize)
-    {
-        for (int i = 0; i < prob->num_variables; ++i)
-        {
-            prob->objective_vector[i] *= -1.0;
-        }
-    }
-
     if (mps_coo_to_csr(prob, &state.coo_matrix, prob->num_constraints) != 0)
     {
         fprintf(stderr, "ERROR: Failed to convert matrix to CSR format.\n");