Burke, James V.; Lewis, Adrian S.; Overton, Michael L. A robust gradient sampling algorithm for nonsmooth, nonconvex optimization. (English) Zbl 1078.65048 SIAM J. Optim. 15, No. 3, 751-779 (2005). 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. Reviewer: Constantin Popa (Constanta) Cited in 5 ReviewsCited in 141 Documents MSC: 65K05 Numerical mathematical programming methods 90C26 Nonconvex programming, global optimization Keywords:subgradient Software:PNEW; Matlab; GradSamp PDFBibTeX XMLCite \textit{J. V. Burke} et al., SIAM J. Optim. 15, No. 3, 751--779 (2005; Zbl 1078.65048) Full Text: DOI