A forward–backward penalty scheme with inertial effects for monotone inclusions. Applications to convex bilevel programming. (3rd October 2019)

• Record Type: Journal Article
• Authors: Boţ, Radu Ioan; Nguyen, Dang-Khoa
• Is Part Of: Optimization. Volume 68:Number 10(2019)
• Page Start: 1855
• Page End: 1880
• Publication Date: 2019-10-03
• Subjects: Maximally monotone operator -- Fitzpatrick function -- forward–backward splitting algorithm -- convex bilevel optimization; 47H05 -- 65K05 -- 90C25; Mathematical optimization -- Periodicals; 519.7
• DOI: 10.1080/02331934.2018.1556662
• Languages: English
• ISSNs: 0233-1934

Abstract

ABSTRACT: We investigate a forward–backward splitting algorithm of penalty type with inertial effects for finding the zeros of the sum of a maximally monotone operator and a cocoercive one and the convex normal cone to the set of zeroes of an another cocoercive operator. Weak ergodic convergence is obtained for the iterates, provided that a condition expressed via the Fitzpatrick function of the operator describing the underlying set of the normal cone is verified. Under strong monotonicity assumptions, strong convergence for the sequence of generated iterates is proved. As a particular instance we consider a convex bilevel minimization problem including the sum of a non-smooth and a smooth function in the upper level and another smooth function in the lower level. We show that in this context weak non-ergodic and strong convergence can be also achieved under inf-compactness assumptions for the involved functions.