Mitk, Semu (PhD)Abraha, Teklebirhan2018-07-182023-11-042018-07-182023-11-042011-01http://etd.aau.edu.et/handle/123456789/9206We 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).enDerivative Free OptimizationThesis