Novel Local-Search-Based Approaches to University Examination Timetabling

Authors:
Massimiliano Caramia;Paolo Dell'Olmo;Giuseppe F. Italiano
Affiliations:
Dipartimento di Ingegneria dell'Impresa, University of Rome “Tor Vergata,” 00133 Rome, Italy;Dipartimento di Statistica, Probabilità e Statistiche Applicate, University of Rome “La Sapienza,” 00185 Rome, Italy;Dipartimento di Informatica, Sistemi e Produzione, University of Rome “Tor Vergata,” 00133 Rome, Italy
Venue:
INFORMS Journal on Computing
Year:
2008

Citing 0
Cited 5

A Developmental Approach to the Uncapacitated Examination Timetabling Problem

Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
A survey of search methodologies and automated system development for examination timetabling

Journal of Scheduling
The revised developmental approach to the uncapacitated examination timetabling problem

Proceedings of the 2009 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists
Examination timetabling using late acceptance hyper-heuristics

CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Selection mechanisms in memory consideration for examination timetabling with harmony search

Proceedings of the 12th annual conference on Genetic and evolutionary computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

Examination timetabling assigns examinations to a given number of time slots so that there are no conflicts. A conflict occurs if a student has to take more than one examination at the same time, or when the number of students that must take an exam exceeds the capacity of the classroom assigned. The objective is to minimize penalties from proximity constraints. We present new algorithms based on local search and report on an extensive experimental study. We consider also a variant where the concern is to produce conflict-free timetables minimizing the number of time slots, regardless of how close exams appear in the schedule. The algorithms proposed also manage the trade-off between the two objective functions and produce the best results on several standard benchmark instances, compared to the best existing algorithms.