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dc.contributor.authorDick, Granten_NZ
dc.date.available2011-04-07T03:02:02Z
dc.date.copyright2003-12en_NZ
dc.identifier.citationDick, G. (2003). An explicit spatial model for niching in genetic algorithms (pp. 151–157). Presented at the 15th Annual Colloquium of the Spatial Information Research Centre (SIRC 2003: Land, Place and Space).en
dc.identifier.urihttp://hdl.handle.net/10523/730
dc.description.abstractA niching technique is an important component of the genetic algorithm when attempting to solve problems that have multiple optimal solutions. Traditional niching techniques use an explicit concept of similarity to perform the actual niche formation. Often, the definition of this similarity function is difficult or requires a priori knowledge of the problem domain. This paper investigates the use of an explicit spatial structure to perform niching. This technique differs from other niching techniques in that it does not require a definition of similarity between individuals in order to form niches. Early results indicate that using this technique can allow a GA to maintain multiple peaks in some multi-modal functions.en_NZ
dc.format.mimetypeapplication/pdf
dc.relation.urihttp://www.business.otago.ac.nz/SIRC05/conferences/2003/28_Dick.pdfen_NZ
dc.subject.lcshQA75 Electronic computers. Computer scienceen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleAn explicit spatial model for niching in genetic algorithmsen_NZ
dc.typeConference or Workshop Item (Paper)en_NZ
dc.description.versionPublisheden_NZ
otago.date.accession2005-11-30en_NZ
otago.relation.pages151-157en_NZ
otago.openaccessOpen
dc.identifier.eprints119en_NZ
dc.description.refereedNon Peer Revieweden_NZ
otago.school.eprintsSpatial Information Research Centreen_NZ
otago.school.eprintsInformation Scienceen_NZ
dc.description.referencesDe Jong, K. A. (1995). An analysis of the behavior of a class of genetic adaptive systems. PhD thesis University of Michigan Ann Arbor. Dissertation Abstracts International 36(10), 5140B; UMI 76-9381. Dick, G. (2003). “The Spatially-Dispersed Genetic Algorithm” In E. Cantú-Paz (ed.), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 2003. Springer Verlag. Dick, G. & Whigham, P. (2002). “Spatially constrained selection in evolutionary computation” Australia-Japan Joint Workshop on Intelligent and Evolving Systems.. Goldberg, D. E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Addison-Wesley. Goldberg, D. E. & Richardson, J. (1987). “Genetic Algorithms with Sharing for Multimodal Function optimization” In J. J. Grefenstette (ed.), Genetic algorithms and their applications: Proc. of the Second Int. Conf. on Genetic Algorithms. Lawrence Erlbaum Assoc. Hillsdale, NJ pp. 41–49. Mahfoud, S. W. (1995). Niching methods for genetic algorithms. PhD thesis University of Illinois at Urbana-Champaign Urbana, IL, USA. IlliGAL Report 95001. *ftp://ftp-illigal.ge.uiuc.edu/pub/papers/IlliGALs/95001.ps.Z Whigham, P. & Dick, G. (2002). “A study of spatial distribution and evolution” The 14th Annual Colloquium of the Spatial Information Research Centre, Wellington, New Zealand.. pp. 157–166.en_NZ
otago.event.dates1-2 December 2003en_NZ
otago.event.placeDunedin, New Zealanden_NZ
otago.event.typeconferenceen_NZ
otago.event.title15th Annual Colloquium of the Spatial Information Research Centre (SIRC 2003: Land, Place and Space)en_NZ
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