The Boolean optimization problem (BOOP) is a highly useful formulation that embraces a variety of 0-1 integer programming problems, including weighted versions of covering, partitioning and maximum satisfiability problems. In 2006 an adaptive memory (tabu search) method for BOOP was introduced, and was proved to be effective compared to competing approaches. However, in the intervening years, major advances have taken place in exact solvers for integer programming problems, leading to widely publicized successes by the leading commercial solvers XPRESS, CPLEX and GUROBI. The implicit message is that an alternative methodology for any broad class of IP problems such as BOOPs would now be dominated by the newer versions of these leading solvers. We test this hypothesis by performing new computational experiments comparing the tabu search method for the BOOP class against XPRESS, CPLEX and GUROBI, and documenting improvements provided by the exact codes. The outcomes are somewhat surprising.