Fair Allocation Algorithms - Demo Website

This repository contains the source code for a demo website showcasing the implementation of five fair allocation algorithms that were added to an open-source Python library - Fairpyx as part of final project for a Computer Science degree.

to the website

to try it yourself go to https://tome.csariel.xyz/

Overview

This project demonstrates the functionality of five new fair allocation algorithms that were added to an existing open-source Python library- Fairpyx.
The website provides an interactive interface where users can input their data, run the algorithms, and view the results.

Algorithms

The following algorithms were implemented as part of this project:

• TTC (Top Trading-Cycle): Assigns one course in each round to each student, the winning students are defined based on the students’ bid values.
• SP (Second Price): In each round distributes one course to each student, with the refund of the bids according to the price of the course.
• TTC-O: Assigns one course in each round to each student, the winning students are defined based on the students’ bid values. Uses linear planning for optimality.
• SP-O: In each round distributes one course to each student, with the refund of the bids according to the price of the course. Uses linear planning for optimality.
• OC (Ordinal-then-Cardinal): In the OC algorithm for CAP, we maximize ordinal utility followed by maximizing cardinal utility among rank-maximal solutions, performing this two-part optimization once for the whole market.

Each algorithm addresses different aspects of fair allocation, providing users with a variety of methods to solve allocation problems.

Technologies Used

Frontend: HTML, CSS, JavaScript
Backend: Flask, Python

Contributors

• Moriya Ester Ohayon
• Tamar Bar-Ilan
• Ofek Kats