Derivative Free Optimization

dc.contributor.advisorMitk, Semu (PhD)
dc.contributor.authorAbraha, Teklebirhan
dc.date.accessioned2018-07-18T08:06:12Z
dc.date.accessioned2023-11-04T12:30:42Z
dc.date.available2018-07-18T08:06:12Z
dc.date.available2023-11-04T12:30:42Z
dc.date.issued2011-01
dc.description.abstractWe will present derivative free algorithms which optimize non-linear unconstrained optimization problems of the following kind: minxEnRmff (ff:R nn→R The algorithms developed for this type of problems are categorized as one-dimensional search (golden section and Fibonacci) methods and multidimensional search methods (Powell’s method and trust region). These algorithms will, hopefully, find the value of for which ff is the lowest. The dimension n of the search space must be lower than some number (say 100). We do NOT have to know the derivatives of We must only have a code which evaluates ff(xx) for a given value ofxx. Each component of the vector must be a continuous real parameter of ff(xx).en_US
dc.identifier.urihttp://etd.aau.edu.et/handle/123456789/9206
dc.language.isoenen_US
dc.publisherAddis Ababa Universityen_US
dc.subjectDerivative Free Optimizationen_US
dc.titleDerivative Free Optimizationen_US
dc.typeThesisen_US

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