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DOI: 10.23952/jnfa.2023.16
Received October 25, 2022; Accepted April 16, 2023; Published May 1, 2023
Abstract. In this paper, we present a self-adaptive algorithm and an inertial version for solving convex bilevel optimization problems. We establish the strong convergence of our proposed algorithms. The step-sizes in our algorithms for the inner level optimization problem are selected without prior knowledge of operator norms. A numerical experiment is included to illustrate the performances of our algorithms and some comparisons are present with related algorithms.
How to Cite this Article:
B. Zhao, P. Duan, Self-adaptive algorithms for solving convex bilevel optimization problems, J. Nonlinear Funct. Anal. 2023 (2023) 16.