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

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  • Ghosh, Diptesh

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 di erent genders, and each solution has a nite life. We compare our genetic algorithms with the best known genetic algorithm for the tool indexing problem and report our computational experience.

Suggested Citation

  • Ghosh, Diptesh, 2016. "Incorporating gender and age in genetic algorithms to solve the indexing problem," IIMA Working Papers WP2016-03-32, Indian Institute of Management Ahmedabad, Research and Publication Department.
    • Handle: RePEc:iim:iimawp:14485
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    File URL: https://www.iima.ac.in/sites/default/files/rnpfiles/14443032282016-03-32.pdf
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    References listed on IDEAS

    as
    1. 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.
    2. Ghosh, Diptesh, 2011. "A Diversification Operator for Genetic Algorithms," IIMA Working Papers WP2011-01-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    3. 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.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Genetic algorithm; permutation problem; crossover; mutation;
    All these keywords.

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