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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21034 AL-RIFAEI_Information_sharing_impact_of_stochastic_diffusion_search_on_differential_evolution_algorithm.pdf - Accepted Version Download (475kB) | Preview |
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 |
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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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