Show simple item record

dc.contributor.authorYang, Shengxiangen
dc.date.accessioned2017-03-23T10:39:06Z
dc.date.available2017-03-23T10:39:06Z
dc.date.issued2002
dc.identifier.citationYang, S. (2002) Primal-dual genetic algorithms for royal road functions. In: E. F. Camacho, L. Basanez, J. A. de la Puente (editors), Proceedings of the 15th IFAC World Congress, Vol. I: Fuzzy, Neural and Genetic Systems, pp. 373-378, Barcelona, Spain, 21-26 July 2002.en
dc.identifier.urihttp://hdl.handle.net/2086/13827
dc.description.abstractBased on Holland's simple genetic algorithm (SGA) there have been many variations developed. Inspired by the phenomenon of diploid genotype and dominance mechanisms broadly existing in nature, we have proposed a primal-dual genetic algorithm (PDGA), see (Yang 2002). Our preliminary experiments based on the Royal Road functions have shown that PDGA outperforms SGA for different performance measures. In this paper we present some further experiment results, especially on the dynamic performance of PDGA over SGA, and give out our explanations and analyses about why PDGA outperforms SGA based on these results. Through the primal-dual mapping between a pair of chromosomes, PDGA's performance of exploration in the search space, especially during the early generations, is improved and thus its total searching efficiency is improved.en
dc.language.isoen_USen
dc.publisherElsevier Science Ltden
dc.subjectGenetic algorithmen
dc.subjectcrossoveren
dc.subjectdominanten
dc.subjectsearchen
dc.subjectparallelismen
dc.subjectoptimizationen
dc.titlePrimal-dual genetic algorithms for royal road functionsen
dc.typeConferenceen
dc.researchgroupCentre for Computational Intelligenceen
dc.peerreviewedYesen
dc.funderN/Aen
dc.projectidN/Aen
dc.cclicenceCC-BY-NCen
dc.researchinstituteInstitute of Artificial Intelligence (IAI)en


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record