Skip to main content

A collection of Operations Research Models & Methods

Project description

Operations Research Models & Methods (ORMM) is inspired by Paul A. Jensen’s Excel Add-ins. His Excel packages were last updated in 2011, and while I believe they do still work, his work may become outdated in a couple of ways:

  • Excel is not as commonly used for OR, except in settings where security is of the utmost concern and/or modern languages like Python, R, Julia, C, C++, MATLAB, AMPL, or other modeling software are not available.

  • From what I understand, Microsoft has been trying to phase out VBA and move to Javascript. If this happens, this could significantly impact whether or not his packages will work.

  • While his website and packages are still available here, some sections are/may become unusable. The animations rely on Flash, which is being phased out in google chrome and other web browsers.

This python package aims to accomplish some of the same goals as Paul Jensen’s website and add-ins did, mainly to

  1. Be an educational tool that shows how abstract models (linear programs, integer programs, nonlinear programs, etc.) can be applied to real-life scenarios to solve complex problems.

  2. Help the practitioner by providing modeling frameworks, methods for solving these models, and problem classes so a user can more easily see how they may be able to frame their business problem/objective through the lens of Operations Research.

This repository contains subpackages for grouping the different types of OR Models & Methods. Currently this subpackage list includes

  1. mathprog: A subpackage for mathematical programs, including linear programs and mixed integer linear programs.

  2. markov: A subpackage for discrete state markov analysis.

  3. network: A subpackage for network models and methods, including the transportation and shortest path tree problems.

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

ormm-0.1.0.tar.gz (53.4 kB view hashes)

Uploaded source

Built Distribution

ormm-0.1.0-py3-none-any.whl (29.6 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page