Volume 25 , Issue 3 , PP: 115-122, 2025 | Cite this article as | XML | Html | PDF | Full Length Article
Ahmed Sabah Ahmed Al-Jilawi 1 *
Doi: https://doi.org/10.54216/IJNS.250311
The aim of this study is to compare common and previously used numerical algorithms for nonlinear problems under different conditions. This study proposes a parallel implementation of two free derivative optimization methods, Powell's method and Nelder-Mead's method, combined with two restart strategies to achieve a global search. In terms of total time, the Powell method converges faster than the Nelder-Mead method. The final function value obtained by the Powell method is slightly lower. Both are optimization techniques used to find the minimum of an objective function in multidimensional space, without requiring derivatives. Also, we extend our results to apply to some neutrosophic non-linear problems under different neutrosophic-based conditions with many examples that explain the validity of our approach.
Numerical Optimization, Nonlinear programming, Approximate methods, Neutrosophic based condition, Neutrosophic non-linear problem
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