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http://ir.futminna.edu.ng:8080/jspui/handle/123456789/8367
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DC Field | Value | Language |
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dc.contributor.author | Abdullahi, Mohammed | - |
dc.contributor.author | Ngadi, Md Asri | - |
dc.contributor.author | Dishing, Salihu Idi | - |
dc.contributor.author | Abdulhamid, Shafi’i Muhammad | - |
dc.contributor.author | Joda, Usman | - |
dc.date.accessioned | 2021-07-11T09:32:57Z | - |
dc.date.available | 2021-07-11T09:32:57Z | - |
dc.date.issued | 2019-05-13 | - |
dc.identifier.citation | http://dx.doi.org/10.1007/s00521-016-2448-8 | en_US |
dc.identifier.issn | 0941-0643 | - |
dc.identifier.uri | http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8367 | - |
dc.description.abstract | Nature-inspired algorithms take inspiration from living things and imitate their behaviours to accomplish robust systems inengineering and computer science discipline. Symbiotic organisms search (SOS) algorithm is a recent metaheuristicalgorithm inspired by symbiotic interaction between organisms in an ecosystem. Organisms develop symbiotic relation-ships such as mutualism, commensalism, and parasitism for their survival in ecosystem. SOS was introduced to solvecontinuous benchmark and engineering problems. The SOS has been shown to be robust and has faster convergence speedwhen compared with genetic algorithm, particle swarm optimization, differential evolution, and artificial bee colony whichare the traditional metaheuristic algorithms. The interests of researchers in using SOS for handling optimization problemsare increasing day by day, due to its successful application in solving optimization problems in science and engineeringfields. Therefore, this paper presents a comprehensive survey of SOS advances and its applications, and this will be ofbenefit to the researchers engaged in the study of SOS algorithm. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Neural Computing and Applications | en_US |
dc.relation.ispartofseries | 32:547–566; | - |
dc.subject | Symbiotic organisms search | en_US |
dc.subject | Global search | en_US |
dc.subject | Metaheuristics algorithms | en_US |
dc.subject | Local search | en_US |
dc.subject | Optimization | en_US |
dc.subject | Bio-inspired algorithms | en_US |
dc.title | A survey of symbiotic organisms search algorithms and applications | en_US |
dc.type | Article | en_US |
Appears in Collections: | Cyber Security Science |
Files in This Item:
File | Description | Size | Format | |
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11.pdf | A survey of symbiotic organisms search algorithms and applications | 866.89 kB | Adobe PDF | View/Open |
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