BayesOpt / nlopt / mma /

Filename Size Date modified Message
759 B
14.3 KB
1.6 KB
Implementation of the globally-convergent method-of-moving-asymptotes (MMA)
algorithm for gradient-based local optimization, as described in:

	Krister Svanberg, "A class of globally convergent optimization
	methods based on conservative convex separable approximations,"
	SIAM J. Optim. 12 (2), p. 555-573 (2002).

In fact, this algorithm is much more general than most of the other
algorithms in NLopt, in that it handles an arbitrary set of nonlinear
(differentiable) constraints as well, in a very efficient manner.
I've implemented the full nonlinear-constrained MMA algorithm, and it
is exported under the nlopt_minimize_constrained API.

It is under the same MIT license as the rest of my code in NLopt (see

Steven G. Johnson
July 2008
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