https://github.com/akshay326/optimization-with-python
Python implementation of classical optimization problems
https://github.com/akshay326/optimization-with-python
linear-programming mixed-integer-programming neos non-convex optimization pyomo solvers
Last synced: 6 months ago
JSON representation
Python implementation of classical optimization problems
- Host: GitHub
- URL: https://github.com/akshay326/optimization-with-python
- Owner: akshay326
- Created: 2019-09-23T17:32:35.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2019-10-20T14:57:46.000Z (about 6 years ago)
- Last Synced: 2025-04-01T23:49:42.932Z (8 months ago)
- Topics: linear-programming, mixed-integer-programming, neos, non-convex, optimization, pyomo, solvers
- Language: Jupyter Notebook
- Homepage:
- Size: 23.4 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Optimization With Python
This repo serves as a collection of [Jupyter](https://jupyter.org/) notebooks containing implementation of classical optimization problems and some research articles. Each folder contains data, model and description for each problem. Most of the implementations are in `Pyomo` and use solvers on [NEOS](https://neos-server.org/neos/solvers/index.html) server.
## How to execute code
The notebooks contains code for installation of required python packages and modelling/execution of the problem.