Please use this identifier to cite or link to this item: http://hdl.handle.net/11718/20268
Title: Comparing genetic algorithm crossover and mutation operators for the indexing problem
Authors: Ghosh, Diptesh
Keywords: Genetic algorithm;Permutation problem;Crossover;Mutation
Issue Date: 18-Mar-2016
Publisher: Indian Institute of Management Ahmedabad
Series/Report no.: W.P.;2016-03-29
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.
URI: http://hdl.handle.net/11718/20268
Appears in Collections:Working Papers

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