A Branch and Bound Algorithm for the Global Optimization of Hessian Lipschitz Continuous Functions

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 overlappin...

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Detalhes bibliográficos
Principais autores: Fowkes, J, Gould, N, Farmer, C
Formato: Journal article
Publicado em: 2012