A python package for operations research and data science problems.
Project description
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:
- Open-source software development.
- Data Science.
- Operations Research.
- Financial Engineering.
- Visualizations in Python or JavaScript.
- 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 and/or 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
-
Greenfield Analysis - a facility location and operation problem. cluster will provide a clustering algorithm for heuristic solutions.
-
Route heuristic for clustering final-destination demand nodes by proximity.
genetic_algorithm
solver
distance
- Haversine distance.
- Distance matrix preprocessing.
Project details
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