/numerical-optimization-techniques

A set of Jupyter notebooks that investigate and compare the performance of several numerical optimization techniques, both unconstrained (univariate search, Powell's method and Gradient Descent (fixed step and optimal step)) and constrained (Exterior Penalty method).

Primary LanguageJupyter NotebookMIT LicenseMIT

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