Abstract | News | Algorithm | Installation | Example | Compilation | Standalone Solver | Documents | Benchmark | Test | License | References | Citation

Abstract

PRINTEMPS (PoRtable INTEger Mathematical Programming Solver) is a C++ metaheuristic modeler/solver library (now with official Python bindings) for general linear integer optimization problems. PRINTEMPS emphasizes the following aspects:

News

Date Update
Jul. 21, 2026 PRINTEMPS v2.9.0 was released.
Feb. 8, 2024 Tabu Search-Based Heuristic Solver for General Integer Linear Programming Problems, a paper on PRINTEMPS, has been published in IEEE Access.

Algorithm

PRINTEMPS can compute approximate solutions for integer linear programming problems using Weighted Tabu Search [1]. For more information on the algorithm, please refer to the paper [2]. The figure below shows the flow-chart of the algorithm of PRINTEMPS.

The flow-chart of the optimization algorithm of PRINTEMPS.

Installation

To install PRINTEMPS for C++, simply clone the repository (or download the latest archive) and then copy the printemps/ directory in the repository to an appropriate location.

For Python, it can be installed from the repository root:

$ pip install ./python

Example

Let us consider a simple linear integer optimization problem [3]:

   (P):   minimize       x_1 + 10 x_2
             x
         subject to   66 x_1 + 14 x_2 >= 1430,
                     -82 x_1 + 28 x_2 >= 1306,
                     x_1 and x_2 are integer.

The following code shows the implementation to solve the problem (P) using PRINTEMPS.

#include <printemps.h>
int main(void) {
    // (1) Modeling
    printemps::model::IPModel model;

    auto& x = model.create_variables("x", 2);
    auto& g = model.create_constraints("g", 2);

    g(0) =  66 * x(0) + 14 * x(1) >= 1430;
    g(1) = -82 * x(0) + 28 * x(1) >= 1306;
    model.minimize(x(0) + 10 * x(1));

    // (2) Running Solver
    auto result = printemps::solver::solve(&model);

    // (3) Accessing the Result
    std::cout << "objective = " << result.solution.objective() << std::endl;
    std::cout << "x(0) = "      << result.solution.variables("x").values(0) << std::endl;
    std::cout << "x(1) = "      << result.solution.variables("x").values(1) << std::endl;

    return 0;
}

By compiling the code above and then running the generated executable, users will obtain the following result:

objective = 707
x(0) = 7
x(1) = 70

The following additional examples are provided in the example/ directory.

Compilation

A C++ program integrating PRINTEMPS can be compiled using a C++17-compatible compiler by specifying the include search path to where PRINTEMPS is located. For instance, the example code example/knapsack.cpp can be built by the following command using g++:

$g++ -std=c++17 -O3 -I path/to/printemps [-fopenmp] sample/knapsack.cpp -o knapsack

Alternatively, you can compile all examples and targets using the root-level Makefile by running make or make example from the repository root.

The option -fopenmp is required to activate parallel computation. See Solver Option Guide for details.

Following combinations of operating systems and compilers are confirmed compilation possible:

Operating System Compiler (version)
macOS 14 gcc 12.4.0, 13.4.0, 14.3.0, 15.1.0
macOS 15 gcc 12.4.0, 13.4.0, 14.3.0, 15.1.0
Ubuntu 22.04 gcc 12.3.0
clang 13.0.1, 14.0.0, 15.0.7
Ubuntu 24.04 gcc 12.3.0, 13.3.0, 14.2.0
clang 16.0.6, 17.0.6, 18.1.3
Windows 2022 gcc 15.2.0 (MSYS2 / mingw64)

Standalone Solver

A standalone executable solver based on PRINTEMPS is also provided. It approximately solves a pure integer programming problem stored in an MPS (Mathematical Programming System) format file. The solver can be built by the following command:

$make application [CC=gcc CXX=g++]

where the options CC and CXX respectively designate the paths of C and C++ compilers, which should be specified according to the user's development environment. The built solver will be generated in build/application/Release/printemps.

The solver can be run by the following command:

$./printemps mps_file [-p option_file] [--accept-continuous]

where the argument mps_file is the path to the MPS file. The argument -p option_file is optional, which specifies solver options and parameters via a JSON file. If the optional flag --accept-continuous is activated, the solver accepts an MPS file that includes continuous variables. Then the continuous variables will be treated as integer variables. An example of solver option JSON file is provided as application/dat/option.json.

Documents

Benchmark

Optimization performance of PRINTEMPS has been evaluated using pure integer instances of MIPLIB 2017. Please refer to Benchmark Results for detail.

Test

The test suites for PRINTEMPS are powered by googletest. GoogleTest will be automatically fetched during configuration. Execute the following command from the repository root to build and run the test suites:

$make run-test [CC=gcc CXX=g++]

License

PRINTEMPS is licensed under MIT license.

References

Contributors

Citation

I would appreciate it if you could cite the following article when referring to PRINTEMPS in your work:

@ARTICLE{10418217,
  author={Koguma, Yuji},
  journal={IEEE Access}, 
  title={Tabu Search-Based Heuristic Solver for General Integer Linear Programming Problems}, 
  year={2024},
  volume={12},
  number={},
  pages={19059-19076},
  doi={10.1109/ACCESS.2024.3361323}}