A Novel Quantum Firefly Algorithm for Global Optimization

Farouq Zitouni, Saad Harous, Ramdane Maamri

Research output: Contribution to journalArticlepeer-review

6 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 languageEnglish
Pages (from-to)8741-8759
Number of pages19
JournalArabian Journal for Science and Engineering
Volume46
Issue number9
DOIs
Publication statusPublished - Sept 2021

Keywords

  • Firefly algorithm
  • Global optimization
  • Metaheuristics
  • Quantum genetic algorithm
  • Test functions

ASJC Scopus subject areas

  • General

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