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DOI 10.5286/raltr.2011020
Persistent URL http://purl.org/net/epubs/work/61295
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Record Id 61295
Title A branch and bound algorithm for the global optimization of Hessian Lipschitz continuous functions
Abstract We present a branch and bound algorithm for the global optimization of a twice differentiable nonconvex objective function with a Lipschitz continuous Hessian over a compact, convex set.The algorithm is based on applying cubic regularisation techniques to the objective function within an overlapping branch and bound algorithm for convex constrained global optimization. Unlike other branch and bound algorithms, lower bounds are obtained via nonconvex underestimators of the function. For a numerical example, we apply the proposed branch and bound algorithm to radial basis function approximations.
Organisation CSE , CSE-NAG , STFC
Funding Information
Related Research Object(s): 66310
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Language English (EN)
Type Details URI(s) Local file(s) Year
Report RAL Technical Reports RAL-TR-2011-020. 2011. RAL-TR-2011-020.pdf 2011