Abstract
We tackle the problem of minimizing a convex nondifferentiable function, for which we present two new bundle type algorithms The novelty of these methods involves a different approach for updating the stability center, that classically is chosen as the best current point (in terms of the objective function). Convergence to a minimum point for both methods, which are related to the concept of proximal trajectory, is proved under routine assumptions. Finally numerical results are reported.
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Fuduli, A., Gaudioso, M. (2000). Fixed and virtual stability center methods for convex nonsmooth minimization. In: Pillo, G.D., Giannessi, F. (eds) Nonlinear Optimization and Related Topics. Applied Optimization, vol 36. Springer, Boston, MA. https://doi.org/10.1007/978-1-4757-3226-9_6
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DOI: https://doi.org/10.1007/978-1-4757-3226-9_6
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