Abstract
In this paper we study an algorithm to find critical points of a lower semicontinuous nonconvex function. We use the Moreau regularization for a special type of functions belonging to the class of prox-regular functions which have very interesting algorithmic properties. We show that it is possible to generate an algorithm in order to obtain a critical point using the theory developed for the composite functions and also the results for the solutions of nonsmooth vectorial equations. We prove the convergence of the algorithm and some estimations of the convergence speed.
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Oscar Cornejo, Z. (2005). An Algorithm for Nonconvex Lower Semicontinuous Optimization Problems. In: Megiddo, N., Xu, Y., Zhu, B. (eds) Algorithmic Applications in Management. AAIM 2005. Lecture Notes in Computer Science, vol 3521. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11496199_5
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DOI: https://doi.org/10.1007/11496199_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26224-4
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