Please use this identifier to cite or link to this item: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8367
Title: A survey of symbiotic organisms search algorithms and applications
Authors: Abdullahi, Mohammed
Ngadi, Md Asri
Dishing, Salihu Idi
Abdulhamid, Shafi’i Muhammad
Joda, Usman
Keywords: Symbiotic organisms search
Global search
Metaheuristics algorithms
Local search
Optimization
Bio-inspired algorithms
Issue Date: 13-May-2019
Publisher: Neural Computing and Applications
Citation: http://dx.doi.org/10.1007/s00521-016-2448-8
Series/Report no.: 32:547–566;
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.
URI: http://repository.futminna.edu.ng:8080/jspui/handle/123456789/8367
ISSN: 0941-0643
Appears in Collections:Cyber Security Science

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