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Fair Allocation Demo

Course Allocation Problem

Problem Overview

In the course allocation problem, a university administrator seeks to efficiently and fairly allocate seats (or items) in over-demanded courses among students (or agents) with heterogeneous preferences.

Algorithms

From the Fairpyx Library

  • 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: 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.

Based on: "Optimization-based Mechanisms for the Course Allocation Problem", by Hoda Atef Yekta, Robert Day (2020) To Read the Paper


To The GitHub Code