A Novel Quantum Firefly Algorithm for Global Optimization

Farouq Zitouni; Saad Harous; Ramdane Maamri

doi:10.1007/s13369-021-05608-5

A Novel Quantum Firefly Algorithm for Global Optimization

Farouq Zitouni, Saad Harous, Ramdane Maamri

Department of Computer Science and Software Engineering

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

A novel nature-inspired metaheuristic optimization algorithm, called the quantum firefly algorithm, is proposed in this paper. The algorithm imitates (a) the social behaviour of fireflies mating in nature, (b) laws of quantum physics, and (c) laws of natural evolution. The algorithm combines the powers of two well-known algorithms: the firefly algorithm and the quantum genetic algorithm. The proposed quantum firefly algorithm’s performance is tested on 15 mathematical test functions and one structural design problem. The obtained results show that the quantum firefly algorithm is very competitive compared to the firefly algorithm and the quantum genetic algorithm.

Original language	English
Pages (from-to)	8741-8759
Number of pages	19
Journal	Arabian Journal for Science and Engineering
Volume	46
Issue number	9
DOIs	https://doi.org/10.1007/s13369-021-05608-5
Publication status	Published - Sept 2021

Keywords

Firefly algorithm
Global optimization
Metaheuristics
Quantum genetic algorithm
Test functions

ASJC Scopus subject areas

General

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10.1007/s13369-021-05608-5

Cite this

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title = "A Novel Quantum Firefly Algorithm for Global Optimization",

abstract = "A novel nature-inspired metaheuristic optimization algorithm, called the quantum firefly algorithm, is proposed in this paper. The algorithm imitates (a) the social behaviour of fireflies mating in nature, (b) laws of quantum physics, and (c) laws of natural evolution. The algorithm combines the powers of two well-known algorithms: the firefly algorithm and the quantum genetic algorithm. The proposed quantum firefly algorithm{\textquoteright}s performance is tested on 15 mathematical test functions and one structural design problem. The obtained results show that the quantum firefly algorithm is very competitive compared to the firefly algorithm and the quantum genetic algorithm.",

keywords = "Firefly algorithm, Global optimization, Metaheuristics, Quantum genetic algorithm, Test functions",

author = "Farouq Zitouni and Saad Harous and Ramdane Maamri",

note = "Funding Information: This research work is supported by UAEU Grant: 31T102-UPAR-1-2017. Publisher Copyright: {\textcopyright} 2021, King Fahd University of Petroleum & Minerals.",

year = "2021",

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doi = "10.1007/s13369-021-05608-5",

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AU - Zitouni, Farouq

AU - Harous, Saad

AU - Maamri, Ramdane

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N2 - A novel nature-inspired metaheuristic optimization algorithm, called the quantum firefly algorithm, is proposed in this paper. The algorithm imitates (a) the social behaviour of fireflies mating in nature, (b) laws of quantum physics, and (c) laws of natural evolution. The algorithm combines the powers of two well-known algorithms: the firefly algorithm and the quantum genetic algorithm. The proposed quantum firefly algorithm’s performance is tested on 15 mathematical test functions and one structural design problem. The obtained results show that the quantum firefly algorithm is very competitive compared to the firefly algorithm and the quantum genetic algorithm.

AB - A novel nature-inspired metaheuristic optimization algorithm, called the quantum firefly algorithm, is proposed in this paper. The algorithm imitates (a) the social behaviour of fireflies mating in nature, (b) laws of quantum physics, and (c) laws of natural evolution. The algorithm combines the powers of two well-known algorithms: the firefly algorithm and the quantum genetic algorithm. The proposed quantum firefly algorithm’s performance is tested on 15 mathematical test functions and one structural design problem. The obtained results show that the quantum firefly algorithm is very competitive compared to the firefly algorithm and the quantum genetic algorithm.

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KW - Global optimization

KW - Metaheuristics

KW - Quantum genetic algorithm

KW - Test functions

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A Novel Quantum Firefly Algorithm for Global Optimization

Abstract

Keywords

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