A comparative study of hyper-heuristics for solving the school timetabling problem

Authors:
Nelishia Pillay
Affiliations:
University of KwaZulu-Natal
Venue:
Proceedings of the South African Institute for Computer Scientists and Information Technologists Conference
Year:
2013

Citing 6
Cited 0

Hopfield neural networks for timetabling: formulations, methods, and comparative results

Computers and Industrial Engineering - Special issue: Focussed issue on applied meta-heuristics
A Tabu-Search Hyperheuristic for Timetabling and Rostering

Journal of Heuristics
An investigation of fuzzy multiple heuristic orderings in the construction of university examination timetables

Computers and Operations Research
An experimental study on hyper-heuristics and exam timetabling

PATAT'06 Proceedings of the 6th international conference on Practice and theory of automated timetabling VI
A study into the use of hyper-heuristics to solve the school timetabling problem

SAICSIT '10 Proceedings of the 2010 Annual Research Conference of the South African Institute of Computer Scientists and Information Technologists
A tabu search hyper-heuristic approach to the examination timetabling problem at the MARA university of technology

PATAT'04 Proceedings of the 5th international conference on Practice and Theory of Automated Timetabling

Quantified Score

Hi-index	0.00

Visualization

Abstract

Hyper-heuristics have proven to be an effective means of obtaining generalized solutions to optimization problems. One such domain in which they have been a success is educational timetabling. However, all the research in this area has focused on university course and examination timetabling. This paper is amongst the first to examine the use of hyper-heuristics to solve the school timetabling problem. The paper compares the performance of a selection constructive hyper-heuristic, a generation constructive hyper-heuristic, a selection perturbative hyper-heuristic and a hybrid hyper-heuristic combining a generation constructive hyper-heuristic and a selection perturbative hyper-heuristic, in solving the school timetabling problem. Each of the hyper-heuristics employs an evolutionary algorithm to search the heuristic space. All four hyper-heuristics were applied to solving the five problems of differing difficulty in the Abramson benchmark set. The selection perturbative hyper-heuristic was found to produce the best results for the all the problems in the benchmark set.