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A new genetic algorithm for the tool 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. This problem has been widely studied in the literature. A genetic algorithm has been suggested in the literature to solve this problem, but its implementation is non-standard. In this paper we describe a permutation based genetic algorithm for the tool indexing problem and compare its performance with an existing genetic algorithm.

Suggested Citation

  • Ghosh, Diptesh, 2016. "A new genetic algorithm for the tool indexing problem," IIMA Working Papers WP2016-03-17, Indian Institute of Management Ahmedabad, Research and Publication Department.
    • Handle: RePEc:iim:iimawp:14437
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    File URL: https://www.iima.ac.in/sites/default/files/rnpfiles/15834390662016-03-17.pdf
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    References listed on IDEAS

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    1. ,, 2004. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 20(2), pages 427-429, April.
    2. Ghosh, Diptesh, 2016. "Exploring Lin Kernighan neighborhoods for the indexing problem," IIMA Working Papers WP2016-02-13, Indian Institute of Management Ahmedabad, Research and Publication Department.
    3. ,, 2004. "Problems And Solutions," Econometric Theory, Cambridge University Press, vol. 20(1), pages 223-229, February.
    4. Ghosh, Diptesh, 2016. "Allocating tools to index positions in tool magazines using tabu search," IIMA Working Papers WP2016-02-06, Indian Institute of Management Ahmedabad, Research and Publication Department.
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    Cited by:

    1. Gintaras Palubeckis, 2020. "An Approach Integrating Simulated Annealing and Variable Neighborhood Search for the Bidirectional Loop Layout Problem," Mathematics, MDPI, vol. 9(1), pages 1-30, December.
    2. Diptesh Ghosh, 2016. "Incorporating gender and age in genetic algorithms to solve the indexing problem," Working Papers id:11034, eSocialSciences.

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