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Stable Convergence of a Primal-Dual Method for Multi-agent Optimization Problems
2022-09-30
We describe a class of primal-dual methods for convex constrained multi-agent optimization problems. We show that these methods possess stable convergence properties under different assumptions. Significant examples of applications are also given.
Ссылка для цитирования:
Konnov I. V. 2022. Stable Convergence of a Primal-Dual Method for Multi-agent Optimization Problems. PREPRINTS.RU. https://doi.org/10.24108/preprints-3112505
Список литературы
1. Konnov, I.V.: Primal-dual method for optimization problems with changing constraints. In: P. Pardalos et al. (eds.) Mathematical Optimization Theory and Operations Research (MOTOR 2022), Lecture Notes in Computer Science, V.13367, pp. 46--61. Springer, Cham (2022)
2. Konnov, I.V.: Variable metric primal-dual method for convex optimization problems with changing constraints. Preprint, stored on 18.08.2022 (Preprints.ru). https://doi.org/10.24108/preprints-3112463. -- 18 pp.
3. Karmanov, V.G.: Mathematical programming. Nauka, Moscow (1986) [In Russian]
4. Polyak, B.T.: Introduction to optimization. Nauka, Moscow (1983) [Engl. transl. in Optimization Software, New York (1987)]