We approach the problem of finding the zeros of the sum of a maximally monotone operator and a monotone and Lipschitz continuous one in a real Hilbert space via an implicit forward-backward-forward dynamical system with nonconstant stepsize function. Besides proving existence and uniqueness of strong global solutions for the differential equation under consideration, we show weak convergence of the generated trajectories and, under strong monotonicity assumptions, strong convergence with exponential rate. In the particular setting of minimizing the sum of a proper, convex and lower semicontinuous function with a smooth convex one, we provide a rate for the convergence of the objective function along the ergodic trajectory to its minimum value.

Contact details are reproduced from the original publication and may be historical.

Radu Ioan Boţ

Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna, Austria

radu.bot@univie.ac.at
  1. B. Abbas, H. Attouch: Dynamical systems and forward-backward algorithms associated with the sum of a convex subdifferential and a monotone cocoercive operator, Optimization 64(10) (2015) 2223–2252.https://doi.org/10.1080/02331934.2014.971412Google Scholar
  2. B. Abbas, H. Attouch, B. F. Svaiter: Newton-like dynamics and forward-backward methods for structured monotone inclusions in Hilbert spaces, J. Optimization Theory Appl. 161(2) (2014) 331–360.https://doi.org/10.1007/s10957-013-0414-5Google Scholar
  3. A. S. Antipin: Minimization of convex functions on convex sets by means of differential equations (Russian), Differentsial’nye Uravneniya 30(9) (1994) 1475–1486; translation in Differential Equations 30(9) (1994) 1365–1375.https://doi.org/10.1016/0005-1098(94)90002-7Google Scholar
  4. H. Attouch, F. Alvarez: The heavy ball with friction dynamical system for convex constrained minimization problems, in: V. H. Nguyen, J.-J. Strodiot, and P. Tossings (eds.), “Optimization (Namur, 1998)”, Lecture Notes Econ. Math. Systems 481, Springer, Berlin (2000) 25–35.https://doi.org/10.1007/978-3-642-57014-8_2Google Scholar
  5. H. Attouch, M. Marques Alves, B. F. Svaiter: A dynamic approach to a proximal-Newton method for monotone inclusions in Hilbert spaces, with complexity O(1/n2), J. Convex Analysis 23(1) (2016) 139–180.https://doi.org/10.68381/jca23006Google Scholar
  6. H. Attouch, B. F. Svaiter: A continuous dynamical Newton-like approach to solving monotone inclusions, SIAM J. Control Optimization 49(2) (2011) 574–598.https://doi.org/10.1137/100784114Google Scholar
  7. H. H. Bauschke, P. L. Combettes: Convex Analysis and Monotone Operator Theory in Hilbert Spaces, CMS Books in Mathematics, Springer (2011).https://doi.org/10.1007/978-1-4419-9467-7Google Scholar
  8. J. Bolte: Continuous gradient projection method in Hilbert spaces, J. Optimization Theory Appl. 119(2) (2003) 235–259.https://doi.org/10.1023/B:JOTA.0000005445.21095.02Google Scholar
  9. R. I. Boţ, E. R. Csetnek: A dynamical system associated with the fixed points set of a nonexpansive operator, J. Dynamics Diff. Equations 29(1) (2017) 155–168.https://doi.org/10.1007/s10884-015-9438-xGoogle Scholar
  10. R. I. Boţ, E. R. Csetnek: Approaching the solving of constrained variational inequalities via penalty term-based dynamical systems, J. Math. Analysis Appl. 435(2) (2016) 1688–1700.https://doi.org/10.1016/j.jmaa.2015.11.032Google Scholar
  11. R. I. Boţ, E. R. Csetnek: Second order forward-backward dynamical systems for monotone inclusion problems, SIAM J. Control Optimization 54(3) (2016) 1423–1443.https://doi.org/10.1137/15M1012657Google Scholar
  12. R. I. Boţ, C. Hendrich: Convergence analysis for a primal-dual monotone and skew splitting algorithm with applications to total variation minimization, J. Math. Imaging Vision 49(3) (2014) 551–568.https://doi.org/10.1007/s10851-013-0486-8Google Scholar
  13. H. Brezis: Opérateurs Maximaux Monotones et Semi-Groupes de Contractions dans les Espaces de Hilbert, Notas de Matemática 50, North Holland (1973).Google Scholar
  14. H. Brezis: Propriétés régularisantes de certains semi-groupes nonlinéaires, Israel J. Math. 9 (1971) 513–534.https://doi.org/10.1007/BF02771467Google Scholar
  15. R. E. Bruck: Asymptotic convergence of nonlinear contraction semigroups in Hilbert spaces, J. Functional Analysis 18 (1975) 15–26.https://doi.org/10.1016/0022-1236(75)90027-0Google Scholar
  16. P. L. Combettes, J.-C. Pesquet: Primal-dual splitting algorithm for solving inclusions with mixtures of composite, Lipschitzian, and parallel-sum type monotone operators, Set-Valued Variational Analysis 20(2) (2012) 307–330.https://doi.org/10.1007/s11228-011-0191-yGoogle Scholar
  17. M. G. Crandall, A. Pazy: Semi-groups of nonlinear contractions and dissipative sets, J. Functional Analysis 3 (1969) 376–418.https://doi.org/10.1016/0022-1236(69)90032-9Google Scholar
  18. A. Haraux: Systémes Dynamiques Dissipatifs et Applications, Recherches en Mathématiques Appliquées, Masson (1991).Google Scholar
  19. M. D. Perlman: Jensen’s inequality for a convex vector-valued function on an infinite-dimensional space, J. Multivariate Analysis 4 (1974) 52–65.https://doi.org/10.1016/0047-259X(74)90005-0Google Scholar
  20. J. Peypouquet, S. Sorin: Evolution equations for maximal monotone operators: asymptotic analysis in continuous and discrete time, J. Convex Analysis 17(3&4) (2010) 1113–1163.https://doi.org/10.68381/jca17068Google Scholar
  21. P. Tseng: A modified forward-backward splitting method for maximal monotone mappings, SIAM J. Control Optimization 38(2) (2000) 431–446.https://doi.org/10.1137/S0363012998338806Google Scholar

S. Banert, R. I. Boţ. “A Forward-Backward-Forward Differential Equation and its Asymptotic Properties.” Journal of Convex Analysis 25 (2018), No. 2, 371–388. https://doi.org/10.68381/jca25026