Title: Hybrid fireworks algorithm with differential evolution operator

Authors: Jinglei Guo; Wei Liu; Ming Liu; Shijue Zheng

Addresses: School of Computer Science, Central China Normal University, Wuhan 430079, China ' School of Computer Science, Central China Normal University, Wuhan 430079, China ' School of Computer Science, Central China Normal University, Wuhan 430079, China ' School of Computer Science, Central China Normal University, Wuhan 430079, China

Abstract: As a population-based intelligence algorithm, fireworks algorithm simulates the fireworks' explosion process to solve optimisation problem. A comprehensive study on enhanced fireworks algorithm (EFWA) reveals that the explosion operator generates too much sparks for the best firework limits the exploration ability. A hybrid version of EFWA (HFWA_DE) is proposed by adding the differential evolution (DE) operator. In HFWA_DE, the population is divided into two subpopulations, then each subpopulation evolves with FWA operator and DE operator separately and exchanges the elitist individual. Experiments on 20 well-known benchmark functions are conducted to illustrate the performance of HFWA_DE. The results turn out HFWA_DE outperforms some state-of-the-art FWAs on most testing functions.

Keywords: fireworks algorithm; DE operator; explosion; exploitation; exploration; intelligent information; optimisation problems; swarm intelligence; hybrid; exchange.

DOI: 10.1504/IJIIDS.2019.102326

International Journal of Intelligent Information and Database Systems, 2019 Vol.12 No.1/2, pp.47 - 64

Received: 08 Oct 2018
Accepted: 13 Feb 2019
Published online: 18 Sep 2019 *

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