Skip to main content

Data-driven APIs for common optimization tasks

Project description

PyPI - Version PyPI - Python Version Tests Docs

gurobi-optimods: data-driven APIs for common optimization tasks

gurobi-optimods is an open-source Python repository of implemented optimization use cases, each with clear, informative, and pretty documentation that explains how to use it and the mathematical model behind it.

Features

gurobi-optimods allows users to:

  • quickly apply optimization to solve a specific problem in their field of interest via intuitive, data-driven APIs
  • learn about the mathematical model behind their use-case through thorough documentation
  • contribute new mods to grow the library

Installation

pip install gurobi-optimods

Dependencies

Documentation

Full documentation for gurobi-optimods is hosted on readthedocs.

License

gurobi-optimods is distributed under the terms of the Apache License 2.0.

Contact Us

For questions related to using gurobi-optimods please use the Gurobi Community Forum.

For reporting bugs, issues and feature requests, specific to gurobi-optimods, please open an issue.

If you encounter issues with Gurobi or gurobipy please contact Gurobi Support.

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

gurobi_optimods-2.2.0.tar.gz (3.9 MB view details)

Uploaded Source

Built Distribution

gurobi_optimods-2.2.0-py3-none-any.whl (275.4 kB view details)

Uploaded Python 3

File details

Details for the file gurobi_optimods-2.2.0.tar.gz.

File metadata

  • Download URL: gurobi_optimods-2.2.0.tar.gz
  • Upload date:
  • Size: 3.9 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.9

File hashes

Hashes for gurobi_optimods-2.2.0.tar.gz
Algorithm Hash digest
SHA256 6f281e44f9f2d0eda1206c5b6ae00d98131be5e4ec1842ee3765a921221b3f91
MD5 9947b72c187f6f7751c697d9f3257889
BLAKE2b-256 9446be7aa34d5a4e2358d6415f37f2cf3da371a061eaecfe255245244aad4e55

See more details on using hashes here.

File details

Details for the file gurobi_optimods-2.2.0-py3-none-any.whl.

File metadata

File hashes

Hashes for gurobi_optimods-2.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 1002117d5806f191cd17b7c094dc873df097eaff287b8a724f85af670c71551e
MD5 90442b20462130e05138442ca8262a4f
BLAKE2b-256 3ac5c5e8c4fc1567fb7243a2485944c1a15b5bfa346760e2f2e0ba37aa88f174

See more details on using hashes here.

Supported by

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