A simulated annealing hyperheuristic methodology for flexible decision support
 Ruibin Bai,
 Jacek Blazewicz,
 Edmund K. Burke,
 Graham Kendall,
 Barry McCollum
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Abstract
Most of the current search techniques represent approaches that are largely adapted for specific search problems. There are many realworld scenarios where the development of such bespoke systems is entirely appropriate. However, there are other situations where it would be beneficial to have methodologies which are generally applicable to more problems. One of our motivating goals for investigating hyperheuristic methodologies is to provide a more general search framework that can be easily and automatically employed on a broader range of problems than is currently possible. In this paper, we investigate a simulated annealing hyperheuristic methodology which operates on a search space of heuristics and which employs a stochastic heuristic selection strategy and a shortterm memory. The generality and performance of the proposed algorithm is demonstrated over a large number of benchmark datasets drawn from two very different and difficult problems, namely; course timetabling and bin packing. The contribution of this paper is to present a method which can be readily (and automatically) applied to different problems whilst still being able to produce results on benchmark problems which are competitive with bespoke human designed tailor made algorithms for those problems.
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 Title
 A simulated annealing hyperheuristic methodology for flexible decision support
 Journal

4OR
Volume 10, Issue 1 , pp 4366
 Cover Date
 20120301
 DOI
 10.1007/s1028801101828
 Print ISSN
 16194500
 Online ISSN
 16142411
 Publisher
 SpringerVerlag
 Additional Links
 Topics
 Keywords

 Hyperheuristics
 Simulated annealing
 Bin packing
 Course timetabling
 9008: Computational methods
 Authors

 Ruibin Bai ^{(1)}
 Jacek Blazewicz ^{(2)}
 Edmund K. Burke ^{(3)}
 Graham Kendall ^{(3)}
 Barry McCollum ^{(4)}
 Author Affiliations

 1. Division of Computer Science, University of Nottingham, Nottingham, NG8 1BB, UK
 2. Institute of Computing Science, Poznan University of Technology, ul. Piotrowo 2, 60965, Poznan, Poland
 3. School of Computer Science, University of Nottingham, Nottingham, NG8 1BB, UK
 4. Department of Electronics, Electrical Engineering and Computer Science, Queen’s University Belfast, Belfast, BT7 1NN, UK