Description Details Author(s) References
Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems. They can also handle box constraints on parameters.
|License:||GPL-2 or greater|
Derivative-Free optimization algorithms. These algorithms do not require gradient information.
More importantly, they can be used to solve non-smooth optimization problems.
These algorithms were translated from the Matlab code of Prof. C.T. Kelley, given in his book "Iterative methods for optimization".
However, there are some non-trivial modifications of the algorithm.
Currently, the Nelder-Mead and Hooke-Jeeves algorithms is implemented. In future, more derivative-free algorithms may be added.
Ravi Varadhan, Johns Hopkins University
Hans W. Borchers, ABB Corporate Research
Maintainer: Ravi Varadhan <email@example.com>
C.T. Kelley (1999), Iterative Methods for Optimization, SIAM.
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