Skip to main content

A library to run and compare optimization models

Project description

Solver Arena

Solver Arena is an open-source library designed to facilitate the performance comparison of different solvers in optimization problems. The library abstracts the implementation of solvers, allowing users to input a list of MPS files and choose the desired solvers with their respective parameters.

Installation

To install the library from PyPI, you can use pipenv with one of the following commands:

  1. Basic Installation (only the main library):

    pipenv install solverarena
    
  2. Installation with a Specific Solver:

    If you want to install the library along with a specific solver, you can use:

    pipenv install solverarena[highs]      # To install with Highs
    pipenv install solverarena[gurobi]     # To install with Gurobi
    pipenv install solverarena[scip]       # To install with SCIP
    pipenv install solverarena[ortools]    # To install with OR-Tools
    
  3. Installation with All Solvers:

    If you want to install the library along with all available solvers, use:

    pipenv install solverarena[all_solvers]
    

Usage

To use the library, you can refer to the example folder, which contains a basic implementation. Here is an example of how to use arena_solver:

from solverarena.run import run_models

if __name__ == "__main__":
    mps_files = [
        "examples/mps_files/model_dataset100.mps",
    ]

    solvers = {
        "highs_default": {
            "solver_name": "highs",
            "presolve": "on",
            "time_limit": 3600,
            "solver": "ipm"
        },
        "highs_no_presolve": {
            "solver_name": "highs",
            "presolve": "off",
            "time_limit": 1800,
            "solver": "simplex"
        }
    }

    results = run_models(mps_files, solvers)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

solverarena-0.2.4.tar.gz (9.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

solverarena-0.2.4-py3-none-any.whl (14.5 kB view details)

Uploaded Python 3

File details

Details for the file solverarena-0.2.4.tar.gz.

File metadata

  • Download URL: solverarena-0.2.4.tar.gz
  • Upload date:
  • Size: 9.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for solverarena-0.2.4.tar.gz
Algorithm Hash digest
SHA256 cad521ff100136b6a5c109e69b5a2fe6d9554240f650f7024c41f4dd79a0ae7f
MD5 fd9a5d2548b91f1269050cd9963dc8df
BLAKE2b-256 a6870bc589a736c48548941d17715e9a3fc95048dfe3c73d13b1c0f95727d70f

See more details on using hashes here.

File details

Details for the file solverarena-0.2.4-py3-none-any.whl.

File metadata

  • Download URL: solverarena-0.2.4-py3-none-any.whl
  • Upload date:
  • Size: 14.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.12.4

File hashes

Hashes for solverarena-0.2.4-py3-none-any.whl
Algorithm Hash digest
SHA256 1687820721cd5639b84a64cfa5840d73ad4a930623cd42b9654d292344a337d9
MD5 c68cb9223c294d400a12fc53881fe139
BLAKE2b-256 46af4db42079082487252da912a4b6bf257a67112fda39b2a460575b25b6e58b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page