  We study the vertex-cover problem which is an NP-hard optimization problem
and a prototypical model exhibiting phase transitions on random graphs, e.g.,
Erdoes-Renyi (ER) random graphs. These phase transitions coincide with changes
of the solution space structure, e.g, for the ER ensemble at connectivity
c=e=2.7183 from replica symmetric to replica-symmetry broken. For the
vertex-cover problem, also the typical complexity of exact branch-and-bound
algorithms, which proceed by exploring the landscape of feasible
configurations, change close to this phase transition from "easy" to "hard". In
this work, we consider an algorithm which has a completely different strategy:
The problem is mapped onto a linear programming problem augmented by a
cutting-plane approach, hence the algorithm operates in a space OUTSIDE the
space of feasible configurations until the final step, where a solution is
found. Here we show that this type of algorithm also exhibits an "easy-hard"
transition around c=e, which strongly indicates that the typical hardness of a
problem is fundamental to the problem and not due to a specific representation
of the problem.
