Master Production Planning

This repository contains various Jupyter Notebooks that explore different production planning strategies. It aims to find the most cost-effective production schedules based on a range of heuristics and methods.

Description

The notebooks in this repository cover multiple production strategies such as:

• One Time Run
• Lot for Lot (Chase)
• Fixed EOQ
• Periodic Order Quantity
• Least Period Cost (Silver-Meal)
• Least Unit Cost
• Part-Period Balancing
• Wagner-Whitin
• Mixed Integer Linear Programming (MILP)

Each notebook includes:

• Calculations of production plans.
• Visualisations of forecasts, productions, and inventory levels.
• Comparisons of costs and efficiencies of different production strategies.

Installation

To run these notebooks, you will need Python and Jupyter installed on your system. You will also need to install the required libraries:

pip install pandas matplotlib

Usage

Clone the repository and navigate to the directory:

git clone https://github.com/your-github-username/production-planning.git
cd production-planning

Start Jupyter Notebook:

jupyter notebook

Open the desired notebook and run the cells to see the results.

Acknowledgements

• This repository was inspired by the coursework and materials provided by the MIT Center for Transportation & Logistics, particularly the MicroMaster in Supply Chain Management's "Supply Chain Design" course.

Licence

This project is licensed under the MIT Licence - see the LICENCE.md file for details.

Notes:

• Replace your-github-username with your actual GitHub username.
• Ensure that all instances of "license" are spelled "licence" to maintain British English consistency, and similarly adjust other terminology as needed.
• You might want to add a LICENCE.md file if you decide to include licensing information.
• Adjust the installation and usage instructions based on your specific setup requirements and preferences.