Conventional CMOS devices are facing an increasing number of challenges as the feature sizes scale down. In the meantime, new nanoscale materials, like graphene nanoribbons (GNR), have been shown to have large integration capability, and thus will probably replace CMOS devices in the future. However, in practice, the GNR wire segments can have a connection defective rate. Particularly, each wire segment has a survival probability, and thus has a chance to fail. This makes the routing in traditional ways very unreliable. In this paper, we study the routing reliability problem and propose an algorithm flow to solve it. Given a s-t routing path on a routing graph, we try to reinforce the reliability of the routing path by adding redundant wiring segments in such a way that its survival probability is maximized with a reasonable overhead of routing resources. Our proposed algorithm flow is two-fold: (1) generation of candidate redundancy segment via min-cost max-flow; (2) optimal selection among the candidates by dynamic programming. The results of extensive experiments confirm the effectiveness and efficiency of our approach.