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MohEsmail143 / 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).
benchmark-functions conda constrained-optimization dejong easom exterior-penalty-function-method golden-section-search gradient-descent jupyter-notebook matplotlib miniconda optimization optimization-methods python rastringin-function rosenbrock-function unconstrained-optimization brainin powell-method univariate-search
Language:Jupyter Notebook