Biologically Inspired Parent Selection in Genetic Algorithms

Zvi Drezner () and Taly Dawn Drezner ()
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Zvi Drezner: California State University-Fullerton
Taly Dawn Drezner: York University

Annals of Operations Research, 2020, vol. 287, issue 1, No 7, 183 pages

Abstract: 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.

Keywords: Genetic algorithms; Hybrid genetic algorithms; Quadratic assignment; Planar p-median (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (6)

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DOI: 10.1007/s10479-019-03343-7

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