First，a modified method for evaluating the importance of each node is presented，and a multi-objective bi-level optimization model for the network reconfiguration is proposed.In the upper-level optimization model，the start-up sequence of generating units is determined by maximizing the restored generation capacity.While in the lower-level，the restoration path is optimized by maximizing the average importance of the candidate restoration path and minimizing the charging capacitance of the same path，and in the formulation the impacts of the restoration path on the restoration of generating units are taken into account.A continuous dynamic Pareto multi-step apoptosis optimization strategy（MSAOP）is next proposed to solve the multi-objective optimization problem of the network reconfiguration problem with multi-step restoration by simulating the physiological characteristics of the cell，and in this way the scale and difficult degree of the optimization problem to be solved can be reduced，and the possible curse of dimensionality avoided as well.This optimization strategy focuses on the stage-wise optimal solution in the restoration path of the generating units，while the global optimality is also taken into account.In addition，the set of network reconfiguration strategies obtained in the restoration procedure can be depicted in the form of a branch graph.Then，a fuzzy decision-making（FDM）method is employed to determine the final network reconfiguration strategy.Finally，the New England 10-unit 39-bus power system and Guangzhou power system are employed to demonstrate the feasibility and efficiency of the developed model and method.