GitHub topics: univariate-search
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).
Language: Jupyter Notebook - Size: 1.71 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0
Related Keywords
benchmark-functions
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brainin
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conda
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constrained-optimization
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dejong
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easom
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exterior-penalty-function-method
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golden-section-search
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gradient-descent
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jupyter-notebook
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matplotlib
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miniconda
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optimization
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optimization-methods
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powell-method
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python
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rosenbrock-function
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unconstrained-optimization
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univariate-search
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