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Supply Chain - Cost/Route Optimization

Overview:

  • Route/Cost Optimization is mainly focused on minimizing/optimizing the overall cost invloved in transport of raw materials from suppliers to factories.
  • Input: An excel file with information about materials, suppliers, factories etc.
  • output: A csv file with information about the quantity that needs to be shipped from each supplier.

Technologies:

Below Technologies/Libraries has been used to develop this application.

  • Python

  • PULP

  • Azure functions

  • Note: For more details about the versions of the libaries used, refer "requirements.txt".

Project Structure:

├── HttpTrigger1
│   └── __init__.py -> contains the functionality to read and write data to the azure blob storage.
│   └── helper_fun.py -> contains all the helper functions which are referred in init.py.
│   └── preprocess.py -> contains all the functions to preprocess the data which are referred in init.py.    
└── azure-pipelines.yml -> contains the deployment steps.
└── requirements.txt -> contains all the required packages to run this application.

To run this application locally:

  • Clone the repository
  • In a terminal, navigate to SCM-Cost-optimization folder
  • Activate your desired virtual environment
  • In the terminal, type pip install -r requirements.txt
  • Run the application with python __init__.py

Deployment:

  • This web application has been deployed using azure pipelines.
  • Under Pipelines => Create a new pipeline-> select Azure repos git -> Slect this repo (SCM-Cost-optimization) -> Select "Python Function App to Linux on Azure"
  • Provide the authorization and select an already created function app from the dropdown.
  • Yml file is generated -> save and run the pipeline.