Competent genetic algorithms for weighing matrices

Kotsireas, IS; Koukouvinos, C; Pardalos, PM; Simos, DE

dc.contributor.author	Kotsireas, IS	en
dc.contributor.author	Koukouvinos, C	en
dc.contributor.author	Pardalos, PM	en
dc.contributor.author	Simos, DE	en
dc.date.accessioned	2014-03-01T11:46:28Z
dc.date.available	2014-03-01T11:46:28Z
dc.date.issued	2011	en
dc.identifier.issn	13826905	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/37927
dc.subject	Competent metaheuristics	en
dc.subject	Fast messy genetic algorithm	en
dc.subject	Messy genetic algorithm	en
dc.subject	Optimization	en
dc.subject	Weighing matrices	en
dc.title	Competent genetic algorithms for weighing matrices	en
heal.type	other	en
heal.identifier.primary	10.1007/s10878-011-9404-4	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s10878-011-9404-4	en
heal.publicationDate	2011	en
heal.abstract	In this paper, we demonstrate that the search for weighing matrices constructed from two circulants can be viewed as a minimization problem together with two competent genetic algorithms to locate optima of an objective function. The motivation to deal with the messy genetic algorithm (mGA) is given from the pioneering results of Goldberg, regarding the ability of the mGA to put tight genes together in a solution which points directly to structural patterns in weighing matrices. In order to take into advantage certain properties of two ternary sequences with zero autocorrelation we use an adaptation of the fast messy GA (fmGA) where we combine mGA with advanced techniques, such as thresholding and tie-breaking. This transformation of the weighing matrices problem to an instance of a combinatorial optimization problem seems to be promising, since we resolved two open cases for weighing matrices as these are listed in the second edition of the Handbook of Combinatorial Designs. © 2011 Springer Science+Business Media, LLC.	en
heal.journalName	Journal of Combinatorial Optimization	en
dc.identifier.doi	10.1007/s10878-011-9404-4	en
dc.identifier.spage	1	en
dc.identifier.epage	18	en