Community Structures Restoration for Enhanced Interdependent Infrastructure Network Resilience

Community structures exist in different infrastructure networks such as water, gas, and power networks among others, where each network is split into multiple sets of components. Such sets are sparsely connected but have densely connected components within each one of them. Such community structures are formed in infrastructure networks based on physical connections within each network or their spatial characteristics, among others. However, infrastructure networks depend on one another for their proper functionality. Though the interdependencies across infrastructure networks can improve their efficiency, they make them highly vulnerable to any disruption. In this project, we will address the interdependent network restoration problem (INRP) from community structures restoration perspective. That is, how to restore community structures in a set of infrastructure networks that are physically interdependent after a disruption with the goal of enhancing their resilience. Accordingly, a mathematical model will be built and formulated for the problem using mixed integer programming (MIP) considering an appropriate set of assumptions. The model is expected to provide: (i) a set of restoration tasks for each infrastructure network, that is selected according to their influence on the performance of their respected networks, (ii) allocate the selected restoration tasks to the available work crews, and (iii) schedule the restoration tasks for each work crew. Furthermore, we will propose a solution approach for the problem that could be utilized to obtain optimal, or near optimal, solutions in a timely manner specially for large scale networks and disruptions. Moreover, community structures as well as their networks could become fully resilient (i.e., reach the highest level of resilience) prior to their complete restoration. That is, there could be some disrupted components are not selected to be restored especially when restoring them does not influence the resilience of its network or other networks. Hence, different restoration strategies for the interdependent networks will be compared: (i) full resilience, restoring only the disrupted component that affect the resilience of the interdependent network, (ii) complete restoration, restoring all disrupted components in each one of the interdependent network, or (iii) a desired level of resilience, restoring a number of disrupted components that is needed to reach a specific level of resilience. The proposed restoration model and solution approach will be demonstrated with a real system of interdependent network from the literature (or generated one in case real data is not available) to evaluate their quality and efficiency.