Please use this identifier to cite or link to this item: http://ir.futminna.edu.ng:8080/jspui/handle/123456789/6050
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dc.contributor.authorAbisoye, Opeyemi Aderiike-
dc.contributor.authorAbisoye, Blessing Olatunde-
dc.date.accessioned2021-07-03T00:43:18Z-
dc.date.available2021-07-03T00:43:18Z-
dc.date.issued2012-12-
dc.identifier.issn1596 - 8308-
dc.identifier.urihttp://repository.futminna.edu.ng:8080/jspui/handle/123456789/6050-
dc.descriptionwww.transcampus.org./journals, www.ajol.info/journals/jorinden_US
dc.description.abstractMany methods are available for finding x*E Rn which minimizes the real value function f(x), some of which are Fibonacci Search Algorithm, Quadratic Search Algorithm, Convergence Algorithm and Cubic Search Algorithm. In this research work, existing algorithms used in single variable optimization problems are critically reviewed. The performance comparison of these algorithms is also examined. The algorithms are implemented using flowcharts and codes in Turbo-C programming language. These algorithms are subjected to convergence text to ascertain their efficiency. The result of the study shows that the algorithms used in single variable optimization problem such as Fibonacci, Quadratic and Cubic Search Method almost coincident. It is concluded that of the three optimization Algorithms, cubic search is the most effective single variable optimization technique.en_US
dc.description.sponsorshipSelfen_US
dc.language.isoenen_US
dc.publisherJORINDen_US
dc.subjectOptimizationen_US
dc.subjectCubicen_US
dc.subjectQuadraticen_US
dc.subjectFibonaccien_US
dc.subjectAlgorithmen_US
dc.titleAN EFFICIENT ALGORITHM FOR SOLVING SINGLE VARIABLE OPTIMIZATION PROBLEMSen_US
dc.typeArticleen_US
Appears in Collections:Computer Engineering

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