“…(v) S i = {x ∈ H | f i (x) ≤ 0}, where f i : H → R is a continuous convex function which is bounded on bounded sets and, for every n ∈ N, T i,pn is a subgradient projector onto S i (see (2.4) In practice, item (i) corresponds to the case when it is relatively easy to compute the best approximation to x from S i (see [3,20,30] for examples); item (ii) corresponds to the monotone inclusion problem 0 ∈ A i x, which arises in many applied mathematics problems [24,52,56]; item (iii) corresponds to equilibrium problems [8,25,39,46]; item (iv) corresponds to (firmly) nonexpansive fixed point problems [36,37] (recall that T is firmly nonexpansive if and only if T = 2T − Id is nonexpansive [37, Theorem 12.1], while Fix T = Fix T ); finally, item (v) corresponds to the inequality f i (x) ≤ 0, which arises in convex inequality systems [21,55] (note that, if dim H < +∞, then bounded sets are relatively compact and thus the boundedness condition on the function is always satisfied).…”