An Electric Vehicle (EV) is an appropriate substitution for traditional transportation means for diminishing greenhouse gas emissions. However, decision-makers are beset by the limited driving range caused by the low battery capacity and the long recharging time. To resolve the former issue, several transportation companies increases the travel distance of the EV by establishing recharging stations in various locations. The proposed Electric Vehicle-Routing Problem with Time Windows (E-VRPTW) and recharging stations are constructed in this context; it augments the VRPTW by reinforcing battery capacity constraints. Meanwhile, super-recharging stations are gradually emerging in the surroundings. They can decrease the recharging time for an EV but consume more energy than regular stations. In this paper, we first extend the E-VRPRTW by adding the elements of super-recharging stations. We then apply a two-stage heuristic algorithm driven by a dynamic programming process to solve the new proposed problem to minimize the travel and total recharging costs. Subsequently, we compare the experimental results of this approach with other algorithms on several sets of benchmark instances. Furthermore, we analyze the impact of super-recharging stations on the total cost of the logistic plan.