Splitting algorithms for solving state-dependent maximal monotone inclusion problems - Li, Xiaoxiao; Dong, Qiao-Li; Gibali, Aviv (Optimization, 2025)
We consider the state-dependent maximal monotone inclusion problem and propose forward-backward splitting algorithms for solving it. Strong convergence of the proposed algorithms is established under suitable conditions. For the special separable case, we present an improved Douglas-Rachford variant that can be easily implemented. Moreover, some accelerated forward-backward splitting algorithms are also presented. Preliminary numerical experiments with comparisons to existing results are presented, illustrating the advantages of our methods.