Abstract (EN)

We propose an improvement of the Approximated Projected Perspective Reformulation (AP2R)of [1] for the case in which constraints linking the binary variables exist. The new approach requires to solve the Perspective Reformulation (PR) once, and then use the corresponding dual information to reformulate the problem prior to applying AP2R, there by combining the root bound quality of the PR with the reduced relaxation computing time of AP2R. Computational results for the cardinality-constrained Mean-Variance portfolio optimization problem show that the new approach is competitivewith state-of-the-art ones.