Smart energy systems can mitigate electric interruption costs provoked by manifold disruptive events via making efforts toward proper pre-disturbance preparation and optimal post-disturbance restoration. In this context, effective contingency management in power distribution networks calls for contemplating disparate parameters from interconnected electric and transportation systems. This chapter, while considering transportation issues in power networks’ field operations, presents a navigation system for pre-positioning resources such as field crews and reconfiguring the network to acquire a more robust configuration in advance of the imminent catastrophe. Also, after the occurrence of the calamity, this navigator optimally allocates the resources to recover the devastating system. So, providing a coordination framework for manual field operation and automation system, this navigator takes a step from traditionally operated systems accommodation toward smart networks. During the contingency management process, there might be modifications in initial data due to the dynamic and time-varying condition of electric and transportation systems. Therefore, the mentioned navigator copes with a real-time problem of data-driven decision making in which, the decisions need to track online changes to the input data. Decision making by the navigation system in this environment is based on a mixed integer linear programming (MILP) optimization which is described in this chapter in detail.