Hybridising heuristics within an estimation distribution algorithm for examination timetabling

Qu, Rong and Pham, Duc Nam Trung and Bai, Ruibin and Kendall, Graham Hybridising heuristics within an estimation distribution algorithm for examination timetabling. Applied Intelligence . ISSN 0924-669X (In Press)

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This paper presents a hybrid hyper-heuristic approach based on estimation distribution algorithms. The main motivation is to raise the level of generality for search methodologies. The objective of the hyper-heuristic is to produce solutions of acceptable quality for a number of optimisation problems. In this work, we demonstrate the generality through experimental results for different variants of exam timetabling problems. The hyper-heuristic represents an automated constructive method that searches for heuristic choices from a given set of low-level heuristics based only on non-domain-specific knowledge. The high-level search methodology is based on a simple estimation distribution algorithm. It is capable of guiding the search to select appropriate heuristics in different problem solving situations. The probability distribution of low-level heuristics at different stages of solution construction can be used to measure their effectiveness and possibly help to facilitate more intelligent hyper-heuristic search methods.

Item Type: Article
Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/s10489-014-0615-0.
Schools/Departments: University of Nottingham, UK > Faculty of Science > School of Computer Science
Identification Number: https://doi.org/10.1007/s10489-014-0615-0
Depositing User: Qu, Rong
Date Deposited: 26 Feb 2015 16:45
Last Modified: 15 Sep 2016 16:18
URI: http://eprints.nottingham.ac.uk/id/eprint/28270

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