6. Conclusion and Future Directions This paper addressed the VRPTW of practic on a real world network with STD travel times. A robust optimization based method was proposed to solve the STD optimal path problem between any pair of customer nodes, which is considered as the subproblem of STDVRPTW, and the path which minimizes the worst-case travel time over all the can didate paths is defined as the optimal. With the subproblem solved, the STDVRPTW can be simplified into a TDVRP and algorithms for such TDVRPs can also be introduced to obtain the solution. Numerical experiments were conducted on the urban transportation network of Shenzhen, China, consisting of3,454 nodes and 4,876 links. The stochastic time dependent link travel times of the network were calibrated at 288 intervals by the use of historical floating car data. Then the NNC algorithm was applied to solve the problem in 4 delivery scenarios. The computational results showed that the proposed STDVRPTW model can improve the level of customers service by guaranteeing the time-window constraint satisfied. The improvement can be very significant especially for large-scale network delivery tasks at no more expense of increases in cost and environmental impacts We would like to continue the work on analyzing STD VRP in large-scale transportation networks using real-time information. More computational tests can be conducted