Basic unconstrained optimization algorithms

Version 1.0.0 (6.94 KB) by Ethem H. Orhan
A Matlab implementation for basic unconstrained optimization algorithms
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Updated 25 Feb 2021

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A Matlab implementation for basic unconstrained optimization algorithms as defined in 'Linear and nonlinear programming by Luenberger and Ye'. The package includes Steepest Descent, Newtons, Fletcher-Reeves and Davidon–Fletcher–Powell algorithms with Fibonacci, Dichotomous, Interval Halving, Newtons and Quadratic line search methods.
To test the methods: Run 'scr_optim.m'

Cite As

Ethem H. Orhan (2024). Basic unconstrained optimization algorithms (https://www.mathworks.com/matlabcentral/fileexchange/87839-basic-unconstrained-optimization-algorithms), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2018a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.0