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Memetic Computing
Erschienen in: Memetic Computing 4/2012

01.12.2012 | Regular Research Paper

Information sharing impact of stochastic diffusion search on differential evolution algorithm

verfasst von: Mohammad Majid al-Rifaie, John Mark Bishop, Tim Blackwell

Erschienen in: Memetic Computing | Ausgabe 4/2012

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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.
Vorheriger Artikel Real-valued genetic algorithms with disagreements

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Fußnoten
1
The ‘information diffusion’ and ‘randomised partial objective function evaluation’ processes enable SDS to more efficiently optimise problems with costly [discrete] objective functions; see stochastic diffusion search section for an introduction to the SDS metaheuristic.
 
2
Test Phase: decides about the status of each SDEAgent, one after another; Diffusion Phase: shares information according to the algorithm presented.
 
3
Hybrid Composition Functions are not used in this work.
 
4
Some of the artistic applications of merging SDS with PSO (falling into the category of generative art) are reported in [1, 2, 4, 5, 8].
 
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Metadaten
Titel
Information sharing impact of stochastic diffusion search on differential evolution algorithm
verfasst von
Mohammad Majid al-Rifaie
John Mark Bishop
Tim Blackwell
Publikationsdatum
01.12.2012
Verlag
Springer-Verlag
Erschienen in
Memetic Computing / Ausgabe 4/2012
Print ISSN: 1865-9284
Elektronische ISSN: 1865-9292
DOI
https://doi.org/10.1007/s12293-012-0094-y

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