with the aim of enlarging the feasible regions without increasing computational complexity. It
is shown that despite the relatively large feasibility gains, the loss in performance may be far
smaller than expected and thus the algorithms give mechanisms for achieving low
computational loads with good feasibility and good performance while using a simple
algorithm set-up. Both algorithms have standard convergence and feasibility guarantees.