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Heuristic space diversity control for improved meta-hyper-heuristic performance

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dc.contributor.author Grobler, J
dc.contributor.author Engelbrecht, AP
dc.contributor.author Kendall, G
dc.contributor.author Yadavallie, VSS
dc.date.accessioned 2016-06-27T08:38:19Z
dc.date.available 2016-06-27T08:38:19Z
dc.date.issued 2015-04
dc.identifier.citation Grobler, J, Engelbrecht, AP, Kendall, G and Yadavallie, VSS. 2015. Heuristic space diversity control for improved meta-hyper-heuristic performance. Information Sciences. Vol 300. pp 49-62 en_US
dc.identifier.uri http://www.sciencedirect.com/science/article/pii/S0020025514010822
dc.identifier.uri http://hdl.handle.net/10204/8576
dc.description Copyright: 2015 Elsevier. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. The definitive version of the work is published in Information Sciences, Vol 300, pp 49-62. en_US
dc.description.abstract This paper expands on the concept of heuristic space diversity and investigates various strategies for the management of heuristic space diversity within the context of a meta-hyper-heuristic algorithm in search of greater performance benefits. Evaluation of various strategies on a diverse set of floating-point benchmark problems shows that heuristic space diversity has a significant impact on hyper-heuristic performance. An exponentially increasing strategy (EIHH) obtained the best results. The value of a priori information about constituent algorithm performance on the benchmark set in question was also evaluated. Finally, EIHH demonstrated good performance when compared to a popular population based algorithm portfolio algorithm and the best performing constituent algorithm. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.ispartofseries Worklist;14964
dc.subject Hyper-heuristics en_US
dc.subject Diversity management en_US
dc.subject Heuristic space diversity en_US
dc.title Heuristic space diversity control for improved meta-hyper-heuristic performance en_US
dc.type Article en_US
dc.identifier.apacitation Grobler, J., Engelbrecht, A., Kendall, G., & Yadavallie, V. (2015). Heuristic space diversity control for improved meta-hyper-heuristic performance. http://hdl.handle.net/10204/8576 en_ZA
dc.identifier.chicagocitation Grobler, J, AP Engelbrecht, G Kendall, and VSS Yadavallie "Heuristic space diversity control for improved meta-hyper-heuristic performance." (2015) http://hdl.handle.net/10204/8576 en_ZA
dc.identifier.vancouvercitation Grobler J, Engelbrecht A, Kendall G, Yadavallie V. Heuristic space diversity control for improved meta-hyper-heuristic performance. 2015; http://hdl.handle.net/10204/8576. en_ZA
dc.identifier.ris TY - Article AU - Grobler, J AU - Engelbrecht, AP AU - Kendall, G AU - Yadavallie, VSS AB - This paper expands on the concept of heuristic space diversity and investigates various strategies for the management of heuristic space diversity within the context of a meta-hyper-heuristic algorithm in search of greater performance benefits. Evaluation of various strategies on a diverse set of floating-point benchmark problems shows that heuristic space diversity has a significant impact on hyper-heuristic performance. An exponentially increasing strategy (EIHH) obtained the best results. The value of a priori information about constituent algorithm performance on the benchmark set in question was also evaluated. Finally, EIHH demonstrated good performance when compared to a popular population based algorithm portfolio algorithm and the best performing constituent algorithm. DA - 2015-04 DB - ResearchSpace DP - CSIR KW - Hyper-heuristics KW - Diversity management KW - Heuristic space diversity LK - https://researchspace.csir.co.za PY - 2015 T1 - Heuristic space diversity control for improved meta-hyper-heuristic performance TI - Heuristic space diversity control for improved meta-hyper-heuristic performance UR - http://hdl.handle.net/10204/8576 ER - en_ZA


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