Hybrid fireworks algorithm with differential evolution operator. (17th September 2019)

• Record Type: Journal Article
• Authors: Guo, Jinglei; Liu, Wei; Liu, Ming; Zheng, Shijue
• Is Part Of: International journal of intelligent information and database systems. Volume 12:Number 1/2(2019)
• Page Start: 47
• Page End: 64
• Publication Date: 2019-09-17
• Subjects: fireworks algorithm -- DE operator -- explosion -- exploitation -- exploration -- intelligent information -- optimisation problems -- swarm intelligence -- hybrid -- exchange; Database management -- Computer programs -- Periodicals; Information retrieval -- Computer programs -- Periodicals; Information storage and retrieval systems -- Computer programs -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Intelligent agents (Computer software) -- Periodicals; 006.33
• Languages: English
• ISSNs: 1751-5858

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.