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Information sharing impact of stochastic diffusion search on differential evolution algorithm

Information sharing impact of stochastic diffusion search on differential evolution algorithm

Al-Rifaie, Mohammad Majid ORCID logoORCID: https://orcid.org/0000-0002-1798-9615, Bishop, John Mark and Blackwell, Tim (2012) Information sharing impact of stochastic diffusion search on differential evolution algorithm. Memetic Computing, 4 (4). pp. 327-338. ISSN 1865-9284 (Print), 1865-9292 (Online) (doi:10.1007/s12293-012-0094-y)

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Abstract

This work details the research aimed at applying the powerful resource allocation mechanism deployed in stochastic diffusion search (SDS) to the differential evolution (DE), effectively merging a nature inspired swarm intelligence algorithm with a biologically inspired evolutionary algorithm. The results reported herein suggest that the hybrid algorithm, exploiting information sharing between the population elements, has the potential to improve the optimisation capability of classical DE algorithms. This claim is verified by running several experiments using state-of-the-art benchmarks. Additionally, the significance of the frequency within which SDS introduces communication and information exchange is also investigated.

Item Type: Article
Uncontrolled Keywords: stochastic diffusion search, differential evolution, optimisation, swarm intelligence
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group: Faculty of Liberal Arts & Sciences > Computational Science & Engineering Group (CSEH)
Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS)
Faculty of Engineering & Science
Last Modified: 04 Mar 2022 13:08
URI: http://gala.gre.ac.uk/id/eprint/21034

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