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arXiv · 2107.03304

The q-Levenberg-Marquardt method for unconstrained nonlinear optimization

Danijela Protic·Miomir Stankovic
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Abstract

A q-Levenberg-Marquardt method is an iterative procedure that blends a q-steepest descent and q-Gauss-Newton methods. When the current solution is far from the correct one the algorithm acts as the q-steepest descent method. Otherwise the algorithm acts as the q-Gauss-Newton method. A damping parameter is used to interpolate between these two methods. The q-parameter is used to escape from local minima and to speed up the search process near the optimal solution.

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Danijela Protic, Miomir Stankovic. 2021-07-05. The q-Levenberg-Marquardt method for unconstrained nonlinear optimization. https://arxiv.org/abs/2107.03304

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