This project was developed as part of a hackathon for COVID19.
The repo consists of three main R scripts: (1) setup, (2) simulation data, and (3) shiny data. The libraries needed to run the simulation are housed in setup.R script.
The simulation.R script, in turn, synthesizes a hypothetical supply and demand dataset for essential items needed during COVID19 pandemic. This was developed in phase I of the project and after further discussions, we decided to make a dashboard based on real product needs. The shiny_data.R script houses a simulation data for shiny app development. The shiny app code is housed in the codevscovid_supply_demand folder consisting of server and ui R scripts.
The app is a simulation of an inventory management system to forecast future (next month's) unit demands and to calculate safety stocks and reorder points.
Our team's final software product, connecting solidarity co-sol can be found here and the video describing it here and here.
Additional improvements to this project can be made by adding regions and geographies to the simulated data and additional machine learning algorithms (e.g. TF) to determine priority of incoming demands and score them to make recommendations.
Please make a pull request or file an issue in this repo for suggestions and/or advice.
Thank you to the talented and inspiring team members who participated in the CodevsCovid19 Zürich Hackathon (Supply and Demand Team). Team members: Noushin Nabavi, Runzhi Yang, Emilien Davaud, Bettsina Walkinson, Dorothee Brumann, Judith Vornberger, Adriatik Dushica, Tim Fuhrmann, Nikhil Mahendran, and Michael Lew.