Skip to content

Fix bug in scaling of dual slacks and sign of dual variables for >= constraints #191

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
rapids-bot merged 1 commit into from
Jul 14, 2025
Merged

Fix bug in scaling of dual slacks and sign of dual variables for >= constraints #191

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
31 changes: 31 additions & 0 deletions cpp/src/dual_simplex/presolve.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -842,6 +842,30 @@ void uncrush_primal_solution(const user_problem_t<i_t, f_t>& user_problem,
std::copy(solution.begin(), solution.begin() + user_problem.num_cols, user_solution.data());
}

template <typename i_t, typename f_t>
void uncrush_dual_solution(const user_problem_t<i_t, f_t>& user_problem,
const lp_problem_t<i_t, f_t>& problem,
const std::vector<f_t>& y,
const std::vector<f_t>& z,
std::vector<f_t>& user_y,
std::vector<f_t>& user_z)
{
// Reduced costs are uncrushed just like the primal solution
uncrush_primal_solution(user_problem, problem, z, user_z);

// Adjust the sign of the dual variables y
// We should have A^T y + z = c
// In convert_user_problem, we converted >= to <=, so we need to adjust the sign of the dual
// variables
for (i_t i = 0; i < user_problem.num_rows; i++) {
if (user_problem.row_sense[i] == 'G') {
user_y[i] = -y[i];
} else {
user_y[i] = y[i];
}
}
}

template <typename i_t, typename f_t>
void uncrush_solution(const presolve_info_t<i_t, f_t>& presolve_info,
const std::vector<f_t>& crushed_x,
Expand Down Expand Up @@ -903,6 +927,13 @@ template void uncrush_primal_solution<int, double>(const user_problem_t<int, dou
const std::vector<double>& solution,
std::vector<double>& user_solution);

template void uncrush_dual_solution<int, double>(const user_problem_t<int, double>& user_problem,
const lp_problem_t<int, double>& problem,
const std::vector<double>& y,
const std::vector<double>& z,
std::vector<double>& user_y,
std::vector<double>& user_z);

template void uncrush_solution<int, double>(const presolve_info_t<int, double>& presolve_info,
const std::vector<double>& crushed_x,
const std::vector<double>& crushed_z,
Expand Down
8 changes: 8 additions & 0 deletions cpp/src/dual_simplex/presolve.hpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -115,6 +115,14 @@ void uncrush_primal_solution(const user_problem_t<i_t, f_t>& user_problem,
const std::vector<f_t>& solution,
std::vector<f_t>& user_solution);

template <typename i_t, typename f_t>
void uncrush_dual_solution(const user_problem_t<i_t, f_t>& user_problem,
const lp_problem_t<i_t, f_t>& problem,
const std::vector<f_t>& y,
const std::vector<f_t>& z,
std::vector<f_t>& user_y,
std::vector<f_t>& user_z);

template <typename i_t, typename f_t>
void uncrush_solution(const presolve_info_t<i_t, f_t>& presolve_info,
const std::vector<f_t>& crushed_x,
Expand Down
2 changes: 1 addition & 1 deletion cpp/src/dual_simplex/scaling.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -88,7 +88,7 @@ void unscale_solution(const std::vector<f_t>& column_scaling,
unscaled_z.resize(n);
for (i_t j = 0; j < n; ++j) {
unscaled_x[j] = scaled_x[j] / column_scaling[j];
unscaled_z[j] = scaled_z[j] / column_scaling[j];
unscaled_z[j] = scaled_z[j] * column_scaling[j];
}
}

Expand Down
4 changes: 2 additions & 2 deletions cpp/src/dual_simplex/solve.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -252,8 +252,8 @@ lp_status_t solve_linear_program(const user_problem_t<i_t, f_t>& user_problem,
lp_status_t status = solve_linear_program_advanced(
original_lp, start_time, settings, lp_solution, vstatus, edge_norms);
uncrush_primal_solution(user_problem, original_lp, lp_solution.x, solution.x);
uncrush_primal_solution(user_problem, original_lp, lp_solution.z, solution.z);
solution.y = lp_solution.y;
uncrush_dual_solution(
user_problem, original_lp, lp_solution.y, lp_solution.z, solution.y, solution.z);
solution.objective = lp_solution.objective;
solution.user_objective = lp_solution.user_objective;
solution.iterations = lp_solution.iterations;
Expand Down
70 changes: 70 additions & 0 deletions cpp/tests/dual_simplex/unit_tests/solve.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -262,4 +262,74 @@ TEST(dual_simplex, empty_columns)
EXPECT_NEAR(solution.x[8], 0, 1e-6);
}

TEST(dual_simplex, dual_variable_greater_than)
{
// minimize 3*x0 + 2 * x1
// subject to x0 + x1 >= 1
// x0 + 2x1 >= 3
// x0, x1 >= 0

cuopt::linear_programming::dual_simplex::user_problem_t<int, double> user_problem;
constexpr int m = 2;
constexpr int n = 2;
constexpr int nz = 4;

user_problem.num_rows = m;
user_problem.num_cols = n;
user_problem.objective.resize(n);
user_problem.objective[0] = 3.0;
user_problem.objective[1] = 2.0;
user_problem.A.m = m;
user_problem.A.n = n;
user_problem.A.nz_max = nz;
user_problem.A.reallocate(nz);
user_problem.A.col_start.resize(n + 1);
user_problem.A.col_start[0] = 0; // x0 start
user_problem.A.col_start[1] = 2;
user_problem.A.col_start[2] = 4;

int nnz = 0;
user_problem.A.i[nnz] = 0;
user_problem.A.x[nnz++] = 1.0;
user_problem.A.i[nnz] = 1;
user_problem.A.x[nnz++] = 1.0;
user_problem.A.i[nnz] = 0;
user_problem.A.x[nnz++] = 1.0;
user_problem.A.i[nnz] = 1;
user_problem.A.x[nnz++] = 2.0;
user_problem.A.print_matrix();
EXPECT_EQ(nnz, nz);

user_problem.rhs.resize(m);
user_problem.rhs[0] = 1.0;
user_problem.rhs[1] = 3.0;

user_problem.row_sense.resize(m);
user_problem.row_sense[0] = 'G';
user_problem.row_sense[1] = 'G';

user_problem.lower.resize(n);
user_problem.lower[0] = 0.0;
user_problem.lower[1] = 0.0;

user_problem.upper.resize(n);
user_problem.upper[0] = dual_simplex::inf;
user_problem.upper[1] = dual_simplex::inf;

user_problem.num_range_rows = 0;
user_problem.problem_name = "dual_variable_greater_than";

dual_simplex::simplex_solver_settings_t<int, double> settings;
dual_simplex::lp_solution_t<int, double> solution(user_problem.num_rows, user_problem.num_cols);
EXPECT_EQ((dual_simplex::solve_linear_program(user_problem, settings, solution)),
dual_simplex::lp_status_t::OPTIMAL);
EXPECT_NEAR(solution.objective, 3.0, 1e-6);
EXPECT_NEAR(solution.x[0], 0.0, 1e-6);
EXPECT_NEAR(solution.x[1], 1.5, 1e-6);
EXPECT_NEAR(solution.y[0], 0.0, 1e-6);
EXPECT_NEAR(solution.y[1], 1.0, 1e-6);
EXPECT_NEAR(solution.z[0], 2.0, 1e-6);
EXPECT_NEAR(solution.z[1], 0.0, 1e-6);
}

} // namespace cuopt::linear_programming::dual_simplex::test