Registrar: a complete-memory operator to enhance performance of genetic algorithms

Charalampakis, AE

dc.contributor.author	Charalampakis, AE	en
dc.date.accessioned	2014-03-01T11:46:29Z
dc.date.available	2014-03-01T11:46:29Z
dc.date.issued	2011	en
dc.identifier.issn	09255001	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/37947
dc.subject	Evolutionary algorithms	en
dc.subject	Genetic algorithms	en
dc.subject	Memory	en
dc.title	Registrar: a complete-memory operator to enhance performance of genetic algorithms	en
heal.type	other	en
heal.identifier.primary	10.1007/s10898-011-9770-6	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s10898-011-9770-6	en
heal.publicationDate	2011	en
heal.abstract	We examine the concept of storing all evaluated chromosomes and directly reuse them in Genetic Algorithms (GAs). This is achieved by a fully encapsulated operator, called Registrar, which is effortlessly placed between the GA and the objective function. The Registrar does not approximate the objective function. Instead, it replaces the chromosomes requested by the GA with similar ones taken from the registry, bypassing the function evaluation. Unlike other methods that use external memory to increase genetic diversity, our simple implementation encourages revisits in order to avoid evaluations in an aggressive manner. Significant increase in performance is observed which is present even at the early stages of evolution, in accordance with the Birthday Problem of probability theory. Implementation with Standard GA shows great promise, while the encapsulation of the code facilitates implementation with other Evolutionary Algorithms. © 2011 Springer Science+Business Media, LLC.	en
heal.journalName	Journal of Global Optimization	en
dc.identifier.doi	10.1007/s10898-011-9770-6	en
dc.identifier.spage	1	en
dc.identifier.epage	35	en