STUDY ON GA BASED SOLUTIONS TO SET PARTITIONING PROBLEM AND PROPOSED                            NEW APPROACH

Nirjon, S.M. Shahriar

dc.contributor.author	Nirjon, S.M. Shahriar
dc.date.accessioned	2012-11-07T09:04:04Z
dc.date.accessioned	2019-05-28T09:31:09Z
dc.date.available	2012-11-07T09:04:04Z
dc.date.available	2019-05-28T09:31:09Z
dc.date.issued	2006-07-01
dc.identifier.uri	http://hdl.handle.net/20.500.11948/437
dc.description.abstract	Evolutionary Algorithms (EAs) are search methods that take their inspiration from natural selection and survival of the fittest in the biological world. Genetic Algorithm is a kind of EA GAs emphasize on the behavioral linkage between the parent generation and their offspring. GAs have been successfully applied to many optimization problems in recent years. In this paper, we work with various GA based solutions used to partition a number of objects into a numbers of disjoint subsets according to some problem specific optimization criteria and we also pose the merits and demerits of these solutions. Later on we propose our own structural approach and show the results.	en_US
dc.language.iso	en	en_US
dc.publisher	Daffodil International University	en_US
dc.subject	Crossover, Fitness function, Genetic Algorithm, Mutation, Population, Selection	en_US
dc.title	STUDY ON GA BASED SOLUTIONS TO SET PARTITIONING PROBLEM AND PROPOSED NEW APPROACH	en_US
dc.type	Article	en_US