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On the life-long learning capabilities of a NELLI*: a hyper-heuristic optimisation system.

Hart, Emma; Sim, Kevin

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Abstract

Real-world applications of optimisation techniques place more importance on finding approaches that result in acceptable quality solutions in a short time-frame and can provide robust solutions, capable of being modified in response to changes in the environment than seeking elusive global optima. We demonstrate that a hyper-heuristic approach NELLI* that takes inspiration from artifical immune systems is capable of life-long learning in an environment where problems are presented in a continuous stream and change over time. Experiments using 1370 bin-packing problems show excellent performance on unseen problems and that the system maintains memory, enabling it to exploit previously learnt heuristics to solve new problems with similar characteristics to ones solved in the past.

Presentation Conference Type Conference Paper (Published)
Start Date Sep 13, 2014
End Date Sep 17, 2014
Publication Date 2014
Deposit Date Jul 1, 2014
Publicly Available Date Dec 31, 2014
Peer Reviewed Peer Reviewed
Volume 8672
Pages 282-291
Book Title Proceedings of PPSN, 13th International Conference on Parallel problem Solving from Nature
ISBN 978-3-319-10761-5
DOI https://doi.org/10.1007/978-3-319-10762-2_28
Keywords Real-world optimisation; hyper-heuristics; NELLI; artificial immune systems;
Public URL http://researchrepository.napier.ac.uk/id/eprint/6902
Publisher URL http://dx.doi.org/10.1007/978-3-319-10762-2_28
Contract Date Jul 1, 2014

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