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 work, we address the interdependent network restoration problem from community structures restoration perspective. That is, how to restore community structures in a set of infrastructure networks that are physically interdependent following a disruption. Accordingly, we propose an optimization model using mixed-integer programming aiming to enhance the resilience of the system of interdependent infrastructure networks. The model provides a set of restoration tasks for each infrastructure network, according to their influence on the performance of their respected networks, and allocates and schedules the selected restoration tasks to the available work crews. The proposed model is demonstrated with a system of interdependent infrastructure networks considering different disruption scenarios.
|Title of host publication||Proceedings of the 11th Annual International Conference on Industrial Engineering and Operations Management, 2021|
|Number of pages||11|
|State||Published - 2021|
|Name||Proceedings of the International Conference on Industrial Engineering and Operations Management|
Bibliographical noteFunding Information:
The author would like to acknowledge the support provided by King Fahd University of Petroleum and Minerals in conducting this research, under project no. SR181021.
© IEOM Society International.
ASJC Scopus subject areas
- Strategy and Management
- Management Science and Operations Research
- Control and Systems Engineering
- Industrial and Manufacturing Engineering