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dc.contributor.authorShakya, Siddhartha
dc.contributor.authorMcCall, John
dc.contributor.authorBrown, Deryck
dc.date.accessioned2009-10-20T09:32:49Z
dc.date.available2009-10-20T09:32:49Z
dc.date.issued2005-09
dc.identifier.citationSHAKYA, S., MCCALL, J. and BROWN, D., 2005. Incorporating a metropolis method in a distribution estimation using Markov random field algorithm. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2005), Volume 3. 2-5 September 2005. New York: IEEE. pp. 2576-2583.en
dc.identifier.isbn0780393635en
dc.identifier.urihttp://hdl.handle.net/10059/432
dc.description.abstractMarkov Random Field (MRF) modelling techniques have been recently proposed as a novel approach to probabilistic modelling for Estimation of Distribution Algorithms (EDAs)[34, 4]. An EDA using this technique, presented in [34], was called Distribution Estimation using Markov Random Fields (DEUM). DEUM was later extended to DEUMd [32, 33]. DEUM and DEUMd use a univariate model of probability distribution, and have been shown to perform better than other univariate EDAs for a range of optimization problems. This paper extends DEUMd to incorporate a simple Metropolis method and empirically shows that for linear univariate problems the proposed univariate MRF models are very effective. In particular, the proposed DEUMd algorithm can find the solution in O(n) fitness evaluations. Furthermore, we suggest that the Metropolis method can also be used to extend the DEUM approach to multivariate problems.en
dc.format.extent177089 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherIEEEen
dc.relation.ispartofProceedings of the IEEE Congress on Evolutionary Computation (CEC 2005)en
dc.rightsCopyright © [2005] IEEE. Reprinted from Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2005) This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of The Robert Gordon University's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.en
dc.titleIncorporating a metropolis method in a distribution estimation using Markov random field algorithm.en
dc.typeConference publicationsen
dc.publisher.urihttp://dx.doi.org/10.1109/CEC.2005.1555017en


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