On Nov 25, 2013, at 9:56 AM, Adel M <[email protected]> wrote: > Is it possible to add constraints to derivative-free optimization algorithms?
Some of them, e.g. COBYLA, already support constraints. It says in the manual which algorithms support nonlinear constraints. Other algorithms like Nelder-Mead in NLopt don't currently support nonlinear constraints, but they could be used in conjunction with the AugLag algorithm to implement constraints. > > I have an optimization problem of an X vector of size n (n >20) and have a > sum constraint on some X[i]: example X[1]+X[2]+..+X[10]=1 A simple linear constraint like that can be implemented by elimination. Just optimize over X[1…9] and set X[10] = 1 - (X[1]+…+X[9]). (Unless there is also a bound constraint on X[10]?)
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