University Course Timetabling with Probability Collectives

Abstract

The Naval Postgraduate School currently uses a time consuming manual process to generate course schedules for students and professors. Each quarter, the process of timetabling approximately 2000 students into nearly 500 courses takes up to 8 weeks. This thesis introduces an automated timetabling algorithm using Probability Collectives (PC) theory. PC Theory is an agent based approach that utilizes Collective Intelligence (COIN) to solve optimization problems by using a collection of agents attempting to achieve a single goal. The algorithm was tested on a set of data provided by the organizers of the 2007 International Timetabling Competition. The algorithm provided valid timetables for every problem instance and successfully scheduled between 70% and 91.6% of all student course requests.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2008
Accession Number
ADA479864

Entities

People

  • Brian M. Autry

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Autonomy
  • Energy and Power Technologies
  • Human Systems

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Commerce
  • Competition
  • Complex Systems
  • Computer Programming
  • Computer Science
  • Computers
  • Genetic Algorithms
  • Integer Programming
  • Linear Programming
  • Multiagent Systems
  • Operations Research
  • Optimization
  • Probability
  • Probability Distributions
  • Students

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation
  • STEM Education