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Biologically Inspired Parent Selection in Genetic Algorithms

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  • Zvi Drezner

    (California State University-Fullerton)

  • Taly Dawn Drezner

    (York University)

Abstract

In this paper we suggest a new rule for parent selection in genetic algorithms inspired by natural evolutionary processes. The new rule is simple to implement in any genetic or hybrid genetic algorithm. We also review some biological principles that inspire genetic algorithms and their extensions. The new rule is tested on the planar p-median problem, also termed the location–allocation problem or the multi-source Weber problem, and the quadratic assignment problem. The genetic algorithm incorporating the new rule provided better results without increasing the computing time including five new best known solutions to well researched problem instances.

Suggested Citation

  • Zvi Drezner & Taly Dawn Drezner, 2020. "Biologically Inspired Parent Selection in Genetic Algorithms," Annals of Operations Research, Springer, vol. 287(1), pages 161-183, April.
    • Handle: RePEc:spr:annopr:v:287:y:2020:i:1:d:10.1007_s10479-019-03343-7
    DOI: 10.1007/s10479-019-03343-7
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    References listed on IDEAS

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    1. U. Dieckmann & M. Doebeli, 1999. "On the Origin of Species by Sympatric Speciation," Working Papers ir99013, International Institute for Applied Systems Analysis.
    2. Zvi Drezner, 2015. "The Quadratic Assignment Problem," Springer Books, in: Gilbert Laporte & Stefan Nickel & Francisco Saldanha da Gama (ed.), Location Science, edition 127, chapter 0, pages 345-363, Springer.
    3. Zakir Hussain Ahmed, 2016. "Experimental analysis of crossover and mutation operators on the quadratic assignment problem," Annals of Operations Research, Springer, vol. 247(2), pages 833-851, December.
    4. Reuven Chen, 1983. "Solution of minisum and minimax location–allocation problems with Euclidean distances," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 30(3), pages 449-459, September.
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    7. Zvi Drezner & Said Salhi, 2017. "Incorporating neighborhood reduction for the solution of the planar p-median problem," Annals of Operations Research, Springer, vol. 258(2), pages 639-654, November.
    8. Marina A. Epelman & Stephen Pollock & Brian Netter & Bobbi S. Low, 2005. "Anisogamy, Expenditure of Reproductive Effort, and the Optimality of Having Two Sexes," Operations Research, INFORMS, vol. 53(3), pages 560-567, June.
    9. Riechmann, Thomas, 2001. "Genetic algorithm learning and evolutionary games," Journal of Economic Dynamics and Control, Elsevier, vol. 25(6-7), pages 1019-1037, June.
    10. Zvi Drezner & Jack Brimberg & Nenad Mladenović & Said Salhi, 2016. "New local searches for solving the multi-source Weber problem," Annals of Operations Research, Springer, vol. 246(1), pages 181-203, November.
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    Cited by:

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    2. Pawel Kalczynski & Jack Brimberg & Zvi Drezner, 2022. "Less is more: discrete starting solutions in the planar p-median problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(1), pages 34-59, April.
    3. Zhuoshi Li & Shizheng Qu & Yinghang Xu & Xinwei Hao & Nan Lin, 2024. "Enhanced Sea Horse Optimization Algorithm for Hyperparameter Optimization of Agricultural Image Recognition," Mathematics, MDPI, vol. 12(3), pages 1-22, January.
    4. Pawel Kalczynski & Zvi Drezner, 2021. "The obnoxious facilities planar p-median problem," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 43(2), pages 577-593, June.
    5. Feifeng Zheng & Zhaojie Wang & Ming Liu, 2022. "Overnight charging scheduling of battery electric buses with uncertain charging time," Operational Research, Springer, vol. 22(5), pages 4865-4903, November.

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