Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/8367
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dc.contributor.authorAbdullahi, Mohammed-
dc.contributor.authorNgadi, Md Asri-
dc.contributor.authorDishing, Salihu Idi-
dc.contributor.authorAbdulhamid, Shafi’i Muhammad-
dc.contributor.authorJoda, Usman-
dc.date.accessioned2021-07-11T09:32:57Z-
dc.date.available2021-07-11T09:32:57Z-
dc.date.issued2019-05-13-
dc.identifier.citationhttp://dx.doi.org/10.1007/s00521-016-2448-8en_US
dc.identifier.issn0941-0643-
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/8367-
dc.description.abstractNature-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.isoenen_US
dc.publisherNeural Computing and Applicationsen_US
dc.relation.ispartofseries32:547–566;-
dc.subjectSymbiotic organisms searchen_US
dc.subjectGlobal searchen_US
dc.subjectMetaheuristics algorithmsen_US
dc.subjectLocal searchen_US
dc.subjectOptimizationen_US
dc.subjectBio-inspired algorithmsen_US
dc.titleA survey of symbiotic organisms search algorithms and applicationsen_US
dc.typeArticleen_US
Appears in Collections:Cyber Security Science

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