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A python package for operations research and data science problems.

Project description

(In Development)

python package

pyords

A library for operations research, data science, and financial engineering.

features

  • pyords.transopt - transportation optimization
  • pyords.netopt - network optimization
  • pyords.schedopt - schedule optimization

implementations

  • graph theory
  • genetic algorithm
  • simulation
  • machine learning

motivation behind the project

Working solo in an engineering team, I want to dedicate a fair amount of time to productionalizing the different skills I've been working on. This library will help me expose myself more to the following:

  1. Open-source software development.
  2. Data Science.
  3. Operations Research.
  4. Financial Engineering.
  5. Visualizations in Python or JavaScript.
  6. Comprehensive self-education of tools such as NumPy, Pandas, D3.js, Matplotlib, IPython and jupyter, scikit-learn and SciPy, git, Google OR Tools (ortools), Pyomo, Supply Chain Guru, Keras, Hadoop, AWS, GCP, Vagrant.

Development & Documentation

Design is up for discussion. I'm going to start by just namespacing most of the unique features implemented. Some currently developed features include the following:

cluster

cluster is aimed at identifying groups in data. See clustering.

current scope

  1. Greenfield Analysis - a facility location and operation problem. cluster will provide a clustering algorithm for heuristic solutions.

  2. Route heuristic for clustering final-destination demand nodes by proximity.

genetic_algorithm

Genetic Algorithm.

solver

  1. Route optimization.

distance

  1. Haversine distance.
  2. Distance matrix preprocessing.

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