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...
| Main Authors: | , , |
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| Format: | Journal article |
| Published: |
2012
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