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Heuristic space diversity management in a meta-hyper-heuristic framework

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dc.contributor.author Grobler, J
dc.contributor.author Engelbrecht, AP
dc.contributor.author Kendall, G
dc.contributor.author Yadavalli, VSS
dc.date.accessioned 2015-03-12T10:09:33Z
dc.date.available 2015-03-12T10:09:33Z
dc.date.issued 2014-07
dc.identifier.citation Grobler, J, Engelbrecht, A.P, Kendall, G and Yadavalli, V.S.S. 2014. Heuristic space diversity management in a meta-hyper-heuristic framework. In: 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing, China, 6-11 July 2014 en_US
dc.identifier.uri http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6900263
dc.identifier.uri http://hdl.handle.net/10204/7938
dc.description 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing, China, 6-11 July 2014. 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. en_US
dc.description.abstract This paper introduces 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. Evaluation on a diverse set of floating-point benchmark problems show that heuristic space diversity has a significant impact on hyper-heuristic performance. The increasing heuristic space diversity strategies performed the best out of all strategies tested. Good performance was also demonstrated with respect to another popular multi-method algorithm and the best performing constituent algorithm. en_US
dc.language.iso en en_US
dc.publisher IEEE Xplore en_US
dc.relation.ispartofseries Workflow;13999
dc.subject Heuristic space diversity en_US
dc.subject Multi-method algorithms en_US
dc.subject Solution space diversity en_US
dc.subject SSD en_US
dc.subject Computation en_US
dc.title Heuristic space diversity management in a meta-hyper-heuristic framework en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Grobler, J., Engelbrecht, A., Kendall, G., & Yadavalli, V. (2014). Heuristic space diversity management in a meta-hyper-heuristic framework. IEEE Xplore. http://hdl.handle.net/10204/7938 en_ZA
dc.identifier.chicagocitation Grobler, J, AP Engelbrecht, G Kendall, and VSS Yadavalli. "Heuristic space diversity management in a meta-hyper-heuristic framework." (2014): http://hdl.handle.net/10204/7938 en_ZA
dc.identifier.vancouvercitation Grobler J, Engelbrecht A, Kendall G, Yadavalli V, Heuristic space diversity management in a meta-hyper-heuristic framework; IEEE Xplore; 2014. http://hdl.handle.net/10204/7938 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Grobler, J AU - Engelbrecht, AP AU - Kendall, G AU - Yadavalli, VSS AB - This paper introduces 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. Evaluation on a diverse set of floating-point benchmark problems show that heuristic space diversity has a significant impact on hyper-heuristic performance. The increasing heuristic space diversity strategies performed the best out of all strategies tested. Good performance was also demonstrated with respect to another popular multi-method algorithm and the best performing constituent algorithm. DA - 2014-07 DB - ResearchSpace DP - CSIR KW - Heuristic space diversity KW - Multi-method algorithms KW - Solution space diversity KW - SSD KW - Computation LK - https://researchspace.csir.co.za PY - 2014 T1 - Heuristic space diversity management in a meta-hyper-heuristic framework TI - Heuristic space diversity management in a meta-hyper-heuristic framework UR - http://hdl.handle.net/10204/7938 ER - en_ZA


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