Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/15816
Appears in Collections:Computing Science and Mathematics Journal Articles
Peer Review Status: Refereed
Title: Monte Carlo hyper-heuristics for examination timetabling
Authors: Burke, Edmund
Kendall, Graham
Misir, Mustafa
Ozcan, Ender
Contact Email: e.k.burke@stir.ac.uk
Keywords: Hyper-heuristics
Simulated annealing
Meta-heuristics
Examination timetabling
Reinforcement learning
Issue Date: Jul-2012
Publisher: Springer
Citation: Burke E, Kendall G, Misir M & Ozcan E (2012) Monte Carlo hyper-heuristics for examination timetabling, Annals of Operations Research, 196 (1), pp. 73-90.
Abstract: Automating the neighbourhood selection process in an iterative approach that uses multiple heuristics is not a trivial task. Hyper-heuristics are search methodologies that not only aim to provide a general framework for solving problem instances at different difficulty levels in a given domain, but a key goal is also to extend the level of generality so that different problems from different domains can also be solved. Indeed, a major challenge is to explore how the heuristic design process might be automated. Almost all existing iterative selection hyper-heuristics performing single point search contain two successive stages; heuristic selection and move acceptance. Different operators can be used in either of the stages. Recent studies explore ways of introducing learning mechanisms into the search process for improving the performance of hyper-heuristics. In this study, a broad empirical analysis is performed comparing Monte Carlo based hyper-heuristics for solving capacitated examination timetabling problems. One of these hyper-heuristics is an approach that overlaps two stages and presents them in a single algorithmic body. A learning heuristic selection method (L) operates in harmony with a simulated annealing move acceptance method using reheating (SA) based on some shared variables. Yet, the heuristic selection and move acceptance methods can be separated as the proposed approach respects the common selection hyper-heuristic framework. The experimental results show that simulated annealing with reheating as a hyper-heuristic move acceptance method has significant potential. On the other hand, the learning hyper-heuristic using simulated annealing with reheating move acceptance (L-SA) performs poorly due to certain weaknesses, such as the choice of rewarding mechanism and the evaluation of utility values for heuristic selection as compared to some other hyper-heuristics in examination timetabling. Trials with other heuristic selection methods confirm that the best alternative for the simulated annealing with reheating move acceptance for examination timetabling is a previously proposed strategy known as the choice function.
Type: Journal Article
URI: http://hdl.handle.net/1893/15816
DOI Link: http://dx.doi.org/10.1007/s10479-010-0782-2
Rights: The publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.
Affiliation: Deputy Principal's Office
University of Nottingham
Yeditepe University
University of Nottingham

Files in This Item:
File Description SizeFormat 
Monte Carlo hyper-heuristics for examination timetabling.pdf810.6 kBAdobe PDFUnder Embargo until 31/12/2999     Request a copy

Note: If any of the files in this item are currently embargoed, you can request a copy directly from the author by clicking the padlock icon above. However, this facility is dependant on the depositor still being contactable at their original email address.

This item is protected by original copyright



Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.