A probabilistic version of the maximal covering location problem is introduced here. The maximum available location problem (MALP) positions p servers in such a way as to maximize the population which will find a server available within a time standard with ℝi>a reliability. The maximum availability problem builds on the probabilistic location set covering problem in concept and on backup covering and expected covering models in technical detail. MALP bears the same relation to the probabilistic location set covering problem as the deterministic maximal covering problem bears to the deterministic location set covering problem. The maximum availability problem is structured here as a zero-one linear programming problem and solved on a medium-sized transportation network representing Baltimore City.
