https://github.com/dufourc1/semesterprojectma3

Comparison of standard combinatorial optimization with reinforcement learning techniques on rescheduling problems as semester project
https://github.com/dufourc1/semesterprojectma3

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Comparison of standard combinatorial optimization with reinforcement learning techniques on rescheduling problems as semester project

• Host: GitHub
• URL: https://github.com/dufourc1/semesterprojectma3
• Owner: dufourc1
• Created: 2019-09-06T13:08:13.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2020-04-28T18:23:47.000Z (about 5 years ago)
• Last Synced: 2025-02-13T23:27:32.093Z (3 months ago)
• Language: Jupyter Notebook
• Homepage:
• Size: 48.5 MB
• Stars: 3
• Watchers: 4
• Forks: 0
• Open Issues: 5
• Metadata Files:
  • Readme: README.md

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README

        
SemesterProjectMA3

==============================

Comparison of standard combinatorial optimization with reinforcement learning techniques on rescheduling problems

Project Organization

------------

    ├── README.md          <- The top-level README for developers using this project.

    ├── data

    │   ├── external       <- Data from third party sources.

    │   ├── interim        <- Intermediate data that has been transformed.

    │   ├── processed      <- The final, canonical data sets for modeling.

    │   └── raw            <- The original, immutable data dump.

    │

    ├── models             <- Trained and serialized models, model predictions, or model summaries

    │

    ├── notebooks          <- Jupyter notebooks. Naming convention is a number (for ordering),

    │                         the creator's initials, and a short `-` delimited description, e.g.

    │                         `1.0-jqp-initial-data-exploration`.

    │

    ├── references         <- Data dictionaries, manuals, and all other explanatory materials.

    │

    ├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.

    │   └── figures        <- Generated graphics and figures to be used in reporting

    │

    ├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.

    │                         generated with `pip freeze > requirements.txt`

    │

    └── src                <- Source code for use in this project.

        │        

        ├── __init__.py    <- Makes src a Python module

        │        

        ├── models         <- Scripts to train models and then use trained models to make

        │   │                 predictions

        │   └── DQL

        │ 

        ├── graph           <- transition graph 

        │ 

        │ 

        ├── flows           <- time expanded graph and linear programs

        │ 

        │ 

        ├── MAPF

        │ 

        │ 

        ├── navigation

        │

        └── visualization  <- Scripts to create exploratory and results oriented visualizations

            └── visualize.py

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Project based on the cookiecutter data science project template. #cookiecutterdatascience