/cuopt-numerical-optimization-api

MPS File Solver

Read and solve LP/MILP problems from standard MPS files using cuOpt.

Problem Description

MPS (Mathematical Programming System) is a standard file format for representing linear and mixed-integer programming problems. This model demonstrates how to:

1. Load an MPS file using Problem.readMPS() (static method)
2. Solve the problem using cuOpt's GPU-accelerated solver
3. Extract and display the solution

This is useful when you have optimization problems in standard MPS format from other solvers, modeling tools, or benchmark libraries like MIPLIB.

MPS File Format

MPS is a column-oriented format with sections:

NAME          problem_name
ROWS
 N  OBJ                    (objective row)
 L  CON1                   (≤ constraint)
 G  CON2                   (≥ constraint)
 E  CON3                   (= constraint)
COLUMNS
    X1        OBJ        1.0
    X1        CON1       2.0
    X2        OBJ        2.0
    X2        CON1       3.0
RHS
    RHS       CON1       10.0
BOUNDS
 LO BND       X1         0.0
 UP BND       X1         5.0
ENDATA

Usage

# Solve the sample problem
python model.py

# Solve a custom MPS file
python model.py --file path/to/problem.mps

# With time limit
python model.py --file problem.mps --time-limit 120

Model Characteristics

• Type: LP or MILP (detected from MPS file)
• Input: Standard MPS file format
• Output: Solution values, objective, status

Sample Problem

The included data/air05.mps is a MIPLIB benchmark (airline crew scheduling):

• Variables: 7,195 (binary)
• Constraints: 426
• Known optimal: 26,374
• Typical solve time: ~2 seconds

Key API Usage

from cuopt.linear_programming.problem import Problem
from cuopt.linear_programming.solver_settings import SolverSettings

# Load MPS file (static method - returns Problem object)
problem = Problem.readMPS("path/to/problem.mps")

# Configure and solve
settings = SolverSettings()
settings.set_parameter("time_limit", 60)
problem.solve(settings)

# Check solution
if problem.Status.name in ["Optimal", "FeasibleFound"]:
    print(f"Objective: {problem.ObjValue}")

Source

Based on cuOpt's built-in MPS support via Problem.readMPS().