We deal with nested affine variational inequalities, i.e., hierarchical problems involving an affine (upper-level) variational inequality whose feasible set is the solution set of another affine (lower-level) variational inequality. We apply this modeling tool to the multi-portfolio selection problem, where the lower-level variational inequality models the Nash equilibrium problem made up by the different accounts, while the upper-level variational inequality is instrumental to perform a selection over this equilibrium set. We propose a projected averaging Tikhonov-like algorithm for the solution of this problem, which only requires the monotonicity of the variational inequalities for both the upper- and the lower-level in order to converge. Finally, we provide complexity properties.
Dettaglio pubblicazione
2022, Optimization in Artificial Intelligence and Data Sciences, Pages 27-36
On Nested Affine Variational Inequalities: The Case of Multi-Portfolio Selection (02a Capitolo o Articolo)
Lampariello L, Priori G, Sagratella S
ISBN: 978-3-030-95379-9; 978-3-030-95380-5
Gruppo di ricerca: Continuous Optimization
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