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Comparing Genetic Algorithm Crossover and Mutation Operators for the Indexing Problem

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  • Ghosh, Diptesh

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.

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  • Ghosh, Diptesh, 2016. "Comparing Genetic Algorithm Crossover and Mutation Operators for the Indexing Problem," IIMA Working Papers WP2016-03-29, Indian Institute of Management Ahmedabad, Research and Publication Department.
    • Handle: RePEc:iim:iimawp:14451
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    File URL: https://www.iima.ac.in/sites/default/files/rnpfiles/4274470042016-03-29.pdf
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    References listed on IDEAS

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    1. Adil Baykasoğlu & Fehmi Burcin Ozsoydan, 2016. "An improved approach for determination of index positions on CNC magazines with cutting tool duplications by integrating shortest path algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 54(3), pages 742-760, February.
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