  We develop a probability-based multi-path location model for an optimal
deployment of alternative fueling stations (AFSs) on a transportation network.
Distinct from prior research efforts in AFS problems, in which all demands are
deemed as given and fixed, this study takes into account that not every node on
the network will be equally probable as a demand node. We explicitly integrates
the probability into the model based on the multi-path refueling location model
to determine the optimal station locations with the goal to maximize the
expected total coverage of all demand nodes on a system level. The resulting
mixed integer linear pro- gram (MILP) is NP-hard. A heuristic based on genetic
algorithm is developed to overcome the computational challenges. We have
conducted extensive numerical experiments based on the benchmark Sioux Falls
network to justify the applicability of the proposed model and heuristic
solution methods.
