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Quantum Genetic Algorithms for Computer Scientists

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Lahoz Beltrá, Rafael (2016) Quantum Genetic Algorithms for Computer Scientists. Computers, 5 (24). ISSN 2073-431X

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Official URL: http://doi.org/10.3390/computers5040024




Abstract

Genetic algorithms (GAs) are a class of evolutionary algorithms inspired by Darwinian natural selection. They are popular heuristic optimisation methods based on simulated genetic mechanisms, i.e., mutation, crossover, etc. and population dynamical processes such as reproduction, selection, etc. Over the last decade, the possibility to emulate a quantum computer (a computer using quantum-mechanical phenomena to perform operations on data) has led to a new class of GAs known as “Quantum Genetic Algorithms” (QGAs). In this review, we present a discussion, future potential, pros and cons of this new class of GAs. The review will be oriented towards computer scientists interested in QGAs “avoiding” the possible difficulties of quantum-mechanical phenomena.


Item Type:Article
Uncontrolled Keywords:quantum genetic algorithms; quantum evolutionary algorithms; reduced quantum genetic algorithm; quantum computing
Subjects:Medical sciences > Biology > Biomathematics
ID Code:45844
Deposited On:19 Dec 2017 15:11
Last Modified:23 Sep 2020 09:01

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