Handling equality constraints by adaptive relaxing rule for swarm algorithms

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dc.creatorXie, Xiao-Feng
dc.creatorZhang, Wen-Jun
dc.creatorBi, De-Chun
dc.date2005-05-25
dc.date.accessioned2026-07-07T03:23:02Z
dc.date.available2026-07-07T03:23:02Z
dc.descriptionThe adaptive constraints relaxing rule for swarm algorithms to handle with the problems with equality constraints is presented. The feasible space of such problems may be similiar to ridge function class, which is hard for applying swarm algorithms. To enter the solution space more easily, the relaxed quasi feasible space is introduced and shrinked adaptively. The experimental results on benchmark functions are compared with the performance of other algorithms, which show its efficiency.
dc.descriptionCongress on Evolutionary Computation, 2004. CEC2004. Volume: 2, On page(s): 2012- 2016 Vol.2
dc.identifierhttps://arxiv.org/abs/cs/0505068
dc.identifierhttp://arxiv.org/abs/cs/0505068
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/32788
dc.subjectNeural and Evolutionary Computing
dc.titleHandling equality constraints by adaptive relaxing rule for swarm algorithms
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