A globally and superlinearly convergent quasi‐Newton method for general box constrained variational inequalities without smoothing approximation

A globally and superlinearly convergent quasi‐Newton method for general box constrained variational inequalities without smoothing approximation

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Article ID: iaor20117995
Volume: 50
Issue: 4
Start Page Number: 675
End Page Number: 694
Publication Date: Aug 2011
Journal: Journal of Global Optimization
Authors: , ,
Keywords: box constraints, global optimization, Newton method, nonsmooth optimization, performance evaluation, quasi-Newton method
Abstract:

A new quasi‐Newton algorithm for the solution of general box constrained variational inequality problem (GVI(l, u, F, f)) is proposed in this paper. It is based on a reformulation of the variational inequality problem as a nonsmooth system of equations by using the median operator. Without smoothing approximation, the proposed quasi‐Newton algorithm is directly applied to solve this class of nonsmooth equations. Under appropriate assumptions, it is proved that the algorithmic sequence globally and superlinearly converges to a solution of the equation reformulation and also of GVI(l, u, F, f). Numerical results show that our new algorithm works quite well.

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