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

Diptesh Ghosh ()

No WP2016-03-32, IIMA Working Papers from Indian Institute of Management Ahmedabad, Research and Publication Department

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.

Keywords: Genetic algorithm; permutation problem; crossover; mutation (search for similar items in EconPapers)
Date: 2016-04-04
New Economics Papers: this item is included in nep-cmp and nep-ore
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Related works:
Working Paper: Incorporating gender and age in genetic algorithms to solve the indexing problem (2016)
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Persistent link: https://EconPapers.repec.org/RePEc:iim:iimawp:14485

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