2017/08/30 by Abdelrahman Eldosouky, Walid Saad, Eldosouky, AbdelRahman +3 · 1 citation
Engineering · Environmental Science · #FOS: Mathematics #Flood Risk Assessment and Management #Optimization and Control (math.OC) #Water Systems and Optimization #Water resources management and optimization
paper · pdf · doi:10.48550/arxiv.1709.00303
openalex publication_date 2017/08/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Instilling resilience in critical infrastructure (CI) such as dams or power\ngrids is a major challenge for tomorrow's cities and communities. Resilience,\nhere, pertains to a CI's ability to adapt or rapidly recover from disruptive\nevents. In this paper, the problem of optimizing and managing the resilience of\nCIs is studied. In particular, a comprehensive two-fold framework is proposed\nto improve CI resilience by considering both the individual CIs and their\ncollective contribution to an entire system of multiple CIs. To this end, a\nnovel analytical resilience index is proposed to measure the effect of each\nCI's physical components on its probability of failure. In particular, a Markov\nchain defining each CI's performance state and a Bayesian network modeling the\nprobability of failure are introduced to infer each CI's resilience index.\nThen, to maximize the resilience of a system of CIs, a novel approach for\nallocating resources, such as drones or maintenance personnel, is proposed. In\nparticular, a comprehensive resource allocation framework, based on the tools\nof contract theory, is proposed enabling the system operator to optimally\nallocate resources, such as, redundant components or monitoring devices to each\nindividual CI based on its economic contribution to the entire system. The\noptimal solution of the contract-based resilience resource allocation problem\nis analytically derived using dynamic programming. The proposed framework is\nthen evaluated using a case study pertaining to hydropower dams and their\ninterdependence to the power grid. Simulation results, within the case study,\nshow that the system operator can economically benefit from allocating the\nresources while dams have a 60% average improvement over their initial\nresilience indices.\n