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dc.contributor.authorDick, Granten_NZ
dc.date.available2011-04-07T03:02:09Z
dc.date.copyright2007-12-06en_NZ
dc.identifier.citationDick, G. (2007). The emergence and distribution of species in a gradient-based spatially-structured evolutionary algorithm (pp. 99–110). Presented at the 19th Annual Colloquium of the Spatial Information Research Centre (SIRC 2007: Does Space Matter?).en
dc.identifier.urihttp://hdl.handle.net/10523/755
dc.description.abstractThe ability to discover and maintain multiple solutions within a single run is a desirable property for evolutionary algorithms. Researchers have previously turned to many biologically-inspired methods for inspiration to produce niching evolutionary algorithms. This paper extends previous work on the Gradient-Based Spatially-Structured Evolutionary Algorithm, which attempts to embody the concept of parapatric speciation within an evolutionary algorithm. Through an comparison of the evolved population with that of an idealised, perfectly proportioned population, we show that the distribution of population members among the niches of a given problem’s fitness landscape does not rely on the global properties of the landscape. Rather, the allocation of individuals to peaks relies on the relative values of neighbouring peaks with regard to their spatial relationship in the fitness landscape.en_NZ
dc.format.mimetypeapplication/pdf
dc.relation.urihttp://www.business.otago.ac.nz/sirc/conferences/2007/20_dick.pdfen_NZ
dc.subjectpopulation structureen_NZ
dc.subjectniching methodsen_NZ
dc.subjectenvironmental gradientsen_NZ
dc.subjectEvolutionary Algorithmsen_NZ
dc.subject.lcshQA76 Computer softwareen_NZ
dc.titleThe emergence and distribution of species in a gradient-based spatially-structured evolutionary algorithmen_NZ
dc.typeConference or Workshop Item (Paper)en_NZ
dc.description.versionPublisheden_NZ
otago.date.accession2009-04-22 04:12:21en_NZ
otago.relation.pages99-110en_NZ
otago.openaccessOpen
dc.identifier.eprints815en_NZ
dc.description.refereedNon Peer Revieweden_NZ
otago.school.eprintsSpatial Information Research Centreen_NZ
otago.school.eprintsInformation Scienceen_NZ
dc.description.referencesCollins, R. J. & Jefferson, D. R. (1991). “Selection in Massively Parallel Genetic Algorithms” In R. K. Belew & L. B. Booker (eds), Proceedings of the Fourth International Conference on Genetic Algorithms. Morgan Kaufmann Publishers San Mateo, CA. Davidor, Y. (1991). “A Naturally Occuring Niche & Species Phenomenon: The Model and First Results” In R. K. Belew & L. B. Booker (eds), Proceedings of the Fourth International Conference on Genetic Algorithms (ICGA’91). Morgan Kaufmann Publishers San Mateo, California pp. 257–263. Deb, K. & Goldberg, D. E. (1989). “An Investigation of Niche and species Formation in Genetic Function Optimization” In J. D. Schaffer (ed.), Proc. of the Third Int. Conf. on Genetic Algorithms. Morgan Kaufmann San Mateo, CA pp. 42–50. Dick, G. & Whigham, P. A. (2005). “The behaviour of genetic drift in a spatially-structured evolutionary algorithm” In D. Corne, Z. Michalewicz, B. McKay, G. Eiben, D. Fogel, C. Fonseca, G. Greenwood, G. Raidl, K. C. Tan & A. Zalzala (eds), Proceedings of the 2005 IEEE Congress on Evolutionary Computation. Vol. 2 IEEE Press Edinburgh, Scotland, UK pp. 1855–1860. Dick, G. & Whigham, P. A. (2006). “Multimodal Optimisation with Structured Populations and Local Environments” In T.-D. Wang, X. Li, S.-H. Chen, X. Wang, H. A. Abbass, H. Iba, G. Chen & X. Yao (eds), SEAL. Vol. 4247 of Lecture Notes in Computer Science Springer. pp. 505–512. Doebeli, M. & Dieckmann, U. (2003). “Speciation along environmental gradients.” Nature. 421(6920): 259–264. Goldberg, D. E. & Richardson, J. (1987). “Genetic algorithms with sharing for multi-modal function optimisation” Proc of the 2nd Int. Conf. on Genetic Algorithms and Their Applications.. pp. 41–49. Kirley, M. (2001). “MEA: A metapopulation evolutionary algorithm for multi-objective optimisation problems” Proceedings of the 2001 IEEE Conference on Evolutionary Computation. IEEE Press Seoul, Korea. Mahfoud, S. W. (1992). “Crowding and preselection revisited” In R. M¨ anner & B. Manderick (eds), Parallel problem solving from nature 2. North-Holland Amsterdam pp. 27–36. Mahfoud, S. W. (1995). “A Comparison of Parallel and Sequential Niching Methods” In L. Eshelman (ed.), Proceedings of the Sixth International Conference on Genetic Algorithms. Morgan Kaufmann San Francisco, CA pp. 136–143. Mayr, E. (1970). Populations, species and evolution; an abridgment of Animal species and evolution. Harvard University Press. Murata, T., Ishibuchi, H. & Gen, M. (2000). “Cellular Genetic Local Search for Multi-Objective Optimization” In D. Whitley, D. Goldberg, E. Cantu-Paz, L. Spector, I. Parmee & H.-G. Beyer (eds), Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2000). Morgan Kaufmann Las Vegas, Nevada, USA pp. 307–314. Murata, T., Ishibuchi, H. & Gen, M. (2001). “Specification of Genetic Search Directions in Cellular Multi-objective Genetic Algorithms” In E. Zitzler, K. Deb, L. Thiele, C. A. C. Coello & D. Corne (eds), First International Conference on Evolutionary Multi-Criterion Optimization. Springer-Verlag. Lecture Notes in Computer Science No. 1993. pp. 82–95.en_NZ
otago.event.dates6-7 Decemberen_NZ
otago.event.placeDunedin, New Zealanden_NZ
otago.event.typeconferenceen_NZ
otago.event.title19th Annual Colloquium of the Spatial Information Research Centre (SIRC 2007: Does Space Matter?)en_NZ
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