Incorporating gender and age in genetic algorithms to solve the indexing problem

IIMA Institutional Repository

Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/20254

Full metadata record

DC Field	Value	Language
dc.contributor.author	Ghosh, Diptesh
dc.date.accessioned	2018-02-06T11:32:02Z
dc.date.available	2018-02-06T11:32:02Z
dc.date.issued	2016-04-04
dc.identifier.uri	http://hdl.handle.net/11718/20254
dc.description.abstract	In this paper we propose new genetic algorithms for the tool indexing problem. Genetic algorithms are said to be nature-inspired, in that they are modeled after the natural process of genetic evolution. The evolution process that they model is asexual in which individuals can potentially live forever. In this paper, we propose a genetic algorithm in which solutions are of two genders, reproduction happens by a combination of solutions with different genders, and each solution has a finite life. We compare our genetic algorithms with the best known genetic algorithm for the tool indexing problem and report our computational experience	en_US
dc.language.iso	en_US	en_US
dc.publisher	Indian Institute of Management Ahmedabad	en_US
dc.relation.ispartofseries	W.P.;2016-03-32
dc.subject	Genetic algorithm	en_US
dc.subject	Permutation problem	en_US
dc.subject	Crossover	en_US
dc.subject	Mutation	en_US
dc.title	Incorporating gender and age in genetic algorithms to solve the indexing problem	en_US
dc.type	Working Paper	en_US
Appears in Collections:	Working Papers

Files in This Item:

File	Description	Size	Format
WP_2016_03_32.pdf	WP_2016_3_32	239.38 kB	Adobe PDF	View/Open