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A Distance-Based Selection of Parents in Genetic Algorithms

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Metaheuristics: Computer Decision-Making

Part of the book series: Applied Optimization ((APOP,volume 86))

Abstract

In this paper we propose an improvement to the widely used metaheuristic genetic algorithm. We suggest a change in the way parents are selected. The method is based on examining the similarity of parents selected for mating. Computational comparisons for solving the quadratic assignment problem using a hybrid genetic algorithm demonstrate the effectiveness of the method. This conclusion is examined statistically. We also report extensive computational results of solving the quadratic assignment problem Thol50. The best variant found the best known solution 8 times out of 20 replications. The average value of the objective function was 0.001% over the best known solution. Run time for this variant is about 18 hours per replication. When run time is increased to about two days per replication the best known solution was found 7 times out of 10 replications with the other three results each being 0.001% over the best known.

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Authors and Affiliations

  1. Department of Information Systems and Decision Sciences, California State University-Fullerton, Fullerton, CA, 92834, USA

    Zvi Drezner & George A. Marcoulides

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  1. Zvi Drezner
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  2. George A. Marcoulides
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Drezner, Z., Marcoulides, G.A. (2003). A Distance-Based Selection of Parents in Genetic Algorithms. In: Metaheuristics: Computer Decision-Making. Applied Optimization, vol 86. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-4137-7_12

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  • DOI: https://doi.org/10.1007/978-1-4757-4137-7_12

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-5403-9

  • Online ISBN: 978-1-4757-4137-7

  • eBook Packages: Springer Book Archive

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