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A robust gradient sampling algorithm for nonsmooth, nonconvex optimization. (English) Zbl 1078.65048

The authors describe a practical and robust algorithm for computing the local minima of a continuously differentiable function in \(n\) real variables, which is not convex and not even locally Lipschitz. The only request formulated is that the gradient of the function is easily computed where it is defined.

MSC:

65K05 Numerical mathematical programming methods
90C26 Nonconvex programming, global optimization

Keywords:

subgradient

Software:

PNEW; Matlab; GradSamp
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