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Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/9890
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dc.contributor.authorMishra, Puneet-
dc.date.accessioned2023-03-22T05:59:41Z-
dc.date.available2023-03-22T05:59:41Z-
dc.date.issued2016-
dc.identifier.urihttps://ieeexplore.ieee.org/abstract/document/7542295-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/9890-
dc.description.abstractMetaheuristic or nature inspired optimization have evolved over time towards development of a general purpose optimizer. In this paper, a novel nature inspired algorithm, based on hunting mechanism of antlions, Ant Lion Optimizer toolkit is developed in LabVIEWTM environment. This paper provides an orderly procedure for development of toolkit including random walk of ants, building of traps, catching of prey and finally rebuilding of traps. LabVIEWTM is a highly productive development environment used largely in measurement and control applications. The only standard optimizer toolkit available in LabVIEW™ is Differential Evolution (DE) and therefore a need was felt to have an efficient optimizer. The toolkit so evolved in this paper when tested on different benchmark functions has performed adequately well over the DE toolkit. The results so obtained clearly prove that the submitted toolkit is able to provide superior results in terms of improved exploration, local optima avoidance, exploitation, and convergence.en_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectEEEen_US
dc.subjectAnt Lion Optimizeren_US
dc.subjectOptimizationen_US
dc.subjectMetaheuristicen_US
dc.subjectVirtual Instrumentsen_US
dc.titleDevelopment of Ant Lion Optimizer toolkit in LabVIEW™en_US
dc.typeArticleen_US
Appears in Collections:Department of Electrical and Electronics Engineering

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