Faculty scheduling using genetic algorithms

Author

Kevin Soule

Abstract

The problem of developing a class schedule for a faculty has been proven to be NP-complete. Therefore when the schedule is large enough, finding just one feasible solution can be impossible for any direct search algorithm within a reasonable time. This project is geared toward investigating the possibility of using genetic-based algorithms to solve faculty scheduling problems of 100 courses or larger quickly. Multiple versions of genetic algorithms and heuristics are tested. Many parameter levels for these algorithms are optimized for fastest convergence.

Publication Date

2006

Document Type

Master's Project

Student Type

Graduate

Department, Program, or Center

Computer Science (GCCIS)

Advisor

Anderson, Peter

Advisor/Committee Member

Radziszowski, Stanislaw

Advisor/Committee Member

Canosa, Roxanne

Comments

Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works in February 2013.

Recommended Citation

Soule, Kevin, "Faculty scheduling using genetic algorithms" (2006). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/6918

Campus

RIT – Main Campus