Comparing genetic algorithm crossover and mutation operators for the indexing problem

dc.contributor.author	Ghosh, Diptesh
dc.date.accessioned	2018-02-07T05:14:56Z
dc.date.available	2018-02-07T05:14:56Z
dc.date.issued	2016-03-18
dc.identifier.uri	http://hdl.handle.net/11718/20268
dc.description.abstract	The tool indexing problem is one of allocating tools to slots in a tool magazine so as to minimize the tool change time in automated machining. Genetic algorithms have been suggested in the literature to solve this problem, but the reasons behind the choice of operators for those algorithms are unclear. In this paper we compare the performances of four common crossover operators and four common mutation operators to find the one most suited for the problem. Our experiments show that the choice of operators for the genetic algorithms presented in the literature is suboptimal.	en_US
dc.language.iso	en_US	en_US
dc.publisher	Indian Institute of Management Ahmedabad	en_US
dc.relation.ispartofseries	W.P.;2016-03-29
dc.subject	Genetic algorithm	en_US
dc.subject	Permutation problem	en_US
dc.subject	Crossover	en_US
dc.subject	Mutation	en_US
dc.title	Comparing genetic algorithm crossover and mutation operators for the indexing problem	en_US
dc.type	Working Paper	en_US