The distribution network restoration is one of the most important parts in the total power system restoration process. The distribution network restoration decomposes into the identification of a suitable network configuration, which is defined by the status of switches between the radially arranged power lines and the optimization of the restoration paths, which are schedules for toggling switches and booting network nodes. This paper presents a two-stage approach for the restoration process of radial high voltage distribution network (e.g. HOkV). A Pareto-based multi-objective genetic algorithm (NSGA-II) is used to optimize the network configuration regarding the load that can be picked up, load priorities, and switching activity. Then, a multi-objective fuzzy decision method (FDM) selects the restoration paths. FDMs choices rely on performance indexes defined by human experts and harmonized as well as linearized by the analytic hierarchy process (AHP). In this work, the node importance degree, the load priority, the influence on already restored network, and the length of distribution lines are considered by FDM. The feasibility and efficiency of the proposed method are validated on the IEEE 30 network
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