Stochastic Diffusion Search Review
Stochastic Diffusion Search, first incepted in 1989, belongs to the extended family of swarm intelligence algorithms. In contrast to many nature-inspired algorithms, stochastic diffusion search has a strong mathematical framework describing its behaviour and convergence. In addition to concisely exp...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2013-12-01
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| Series: | Paladyn |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/pjbr-2013-0021 |
| _version_ | 1797428403407683584 |
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| author | al-Rifaie Mohammad Majid Bishop John Mark |
| author_facet | al-Rifaie Mohammad Majid Bishop John Mark |
| author_sort | al-Rifaie Mohammad Majid |
| collection | DOAJ |
| description | Stochastic Diffusion Search, first incepted in 1989, belongs to the extended family of swarm intelligence algorithms.
In contrast to many nature-inspired algorithms, stochastic diffusion search has a strong mathematical framework
describing its behaviour and convergence. In addition to concisely exploring the algorithm in the context of natural
swarm intelligence systems, this paper reviews various developments of the algorithm, which have been shown to
perform well in a variety of application domains including continuous optimisation, implementation on hardware and
medical imaging. This algorithm has also being utilised to argue the potential computational creativity of swarm
intelligence systems through the two phases of exploration and exploitation. |
| first_indexed | 2024-03-09T08:58:23Z |
| format | Article |
| id | doaj.art-aa70677ac8df42768e2bbd143126dd96 |
| institution | Directory Open Access Journal |
| issn | 2081-4836 |
| language | English |
| last_indexed | 2024-03-09T08:58:23Z |
| publishDate | 2013-12-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Paladyn |
| spelling | doaj.art-aa70677ac8df42768e2bbd143126dd962023-12-02T12:28:40ZengDe GruyterPaladyn2081-48362013-12-014315517310.2478/pjbr-2013-0021Stochastic Diffusion Search Reviewal-Rifaie Mohammad Majid0Bishop John Mark1Goldsmiths College, University of London New Cross Gate, London SE14 6NW, United KingdomGoldsmiths College, University of London New Cross Gate, London SE14 6NW, United KingdomStochastic Diffusion Search, first incepted in 1989, belongs to the extended family of swarm intelligence algorithms. In contrast to many nature-inspired algorithms, stochastic diffusion search has a strong mathematical framework describing its behaviour and convergence. In addition to concisely exploring the algorithm in the context of natural swarm intelligence systems, this paper reviews various developments of the algorithm, which have been shown to perform well in a variety of application domains including continuous optimisation, implementation on hardware and medical imaging. This algorithm has also being utilised to argue the potential computational creativity of swarm intelligence systems through the two phases of exploration and exploitation.https://doi.org/10.2478/pjbr-2013-0021swarm intelligenceresource allocationoptimisationsearchinformation exchange |
| spellingShingle | al-Rifaie Mohammad Majid Bishop John Mark Stochastic Diffusion Search Review Paladyn swarm intelligence resource allocation optimisation search information exchange |
| title | Stochastic Diffusion Search Review |
| title_full | Stochastic Diffusion Search Review |
| title_fullStr | Stochastic Diffusion Search Review |
| title_full_unstemmed | Stochastic Diffusion Search Review |
| title_short | Stochastic Diffusion Search Review |
| title_sort | stochastic diffusion search review |
| topic | swarm intelligence resource allocation optimisation search information exchange |
| url | https://doi.org/10.2478/pjbr-2013-0021 |
| work_keys_str_mv | AT alrifaiemohammadmajid stochasticdiffusionsearchreview AT bishopjohnmark stochasticdiffusionsearchreview |