We pursue the study of concavity cuts for the disjoint bilinear programming
problem. This optimization problem has two equivalent symmetric linens max
min reformulations, leading to two sets of concavity cuts. We first examine
the depth of these cuts by considering the assumptions on the boundedness
of the feasible regions of both maxmin and bilinear formulations. We next p
ropose a branch and bound algorithm which make use of concavity cuts. We al
so present a procedure that eliminates degenerate solutions. Extensive comp
utational experiences are reported. Sparse problems with up to 500 variable
s in each disjoint sets and 100 constraints, and dense problems with up to
60 variables again in each sets and 60 constraints are solved in reasonable
computing times.