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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: 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:https://doi.org/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 / Department / Research Group: Faculty of Liberal Arts & Sciences
Faculty of Liberal Arts & Sciences > Centre for Computer & Computational Science
Faculty of Liberal Arts & Sciences > School of Computing & Mathematical Sciences (CAM)
Last Modified: 21 Jul 2021 21:31
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
Selected for REF2021: None
URI: http://gala.gre.ac.uk/id/eprint/21034

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