Protection-interdiction-restoration: Tri-level optimization for enhancing interdependent network resilience

Ghorbani-Renani, Nafiseh; González, Andrés D.; Barker, Kash; Morshedlou, Nazanin

doi:10.1016/j.ress.2020.106907

Cited by 67 publications

(19 citation statements)

References 62 publications

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“…The main objectives generally drive the restoration of infrastructure networks is to restore the network components as quickly as possible so that user demand from the network is reinstated. In this regard, some have designed their objective function to impose a cost for every period in which user demand is not satisfied [ 15 , 16 , 19 , 20 , 58 – 61 ]. The other angles of this problem that have been generally illustrated in the constraints of these models are (i) network flow cost, (ii) interdependency, (iii) crew constraints, and (iv) resource and budget constraints, among others.…”

Section: Interdependent Network Adaptive Recovery Modelmentioning

confidence: 99%

Adaptive algorithm for dependent infrastructure network restoration in an imperfect information sharing environment

2022

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Critical infrastructure networks are vital for a functioning society and their failure can have widespread consequences. Decision-making for critical infrastructure resilience can suffer based on several characteristics exhibited by these networks, including (i) that there exist interdependencies with other networks, (ii) that several decision-makers represent potentially competing interests among the interdependent networks, and (iii) that information about other decision-makers’ actions are uncertain and potentially unknown. To address these concerns, we propose an adaptive algorithm using machine learning to integrate predictions about other decision-makers’ behavior into an interdependent network restoration planning problem considering an imperfect information sharing environment. We examined our algorithm against the optimal solution for various types, sizes, and dependencies of networks, resulting in insignificant differences. To assess the proposed algorithm’s efficiency, we compared its results with a proposed heuristic method that prioritizes, and schedules components restoration based on centrality-based importance measures. The proposed algorithm provides a solution sufficiently close to the optimal solution showing the algorithm performs well in situations where the information sharing environment is incomplete.

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Section: Interdependent Network Adaptive Recovery Modelmentioning

confidence: 99%

Adaptive algorithm for dependent infrastructure network restoration in an imperfect information sharing environment

2022

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“…For example, if power was out to a substation, then certain components within the water network would no longer be available. Ghorbani‐Renani et al [93] examine DAD models for interdependent networks that specifically capture the rebound process after the perturbation. We refer the reader to the review of Ouyang [162] that discusses modeling approaches for interdependent infrastructures.…”

Section: Optimization Models and Network Robustnessmentioning

confidence: 99%

“…Loggins et al [138] have created interdependent restoration models that account for social infrastructure that rely on civil infrastructure systems. Ghorbani‐Renani et al [93] examine rebound for interdependent networks as the inner problem within a DAD model. For a comprehensive overview of work related to interdependent networks, we point the reader to Ouyang [162].…”

Section: Optimization Models and Network Reboundmentioning

confidence: 99%

In search of network resilience: An optimization‐based view

et al. 2020

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Fifty years of research in Networks coincides with 50 years of advances in resilience theory and applications. The purpose of this review is to identify how these two technical communities influenced each other in the past and can bolster each other in the future. Advances in resilience theory show that there are at least four ways networks demonstrate resilience: robustness, rebound, extensibility, and adaptability. Research published in Networks and by the broader network optimization community has focused primarily on technical methods for robustness and rebound. We review this literature to organize seminal problems and papers on the ability of networks to manage increasing stressors and return to normal activities after a stressful event. In contrast, the Networks community has made less progress addressing issues for network extensibility and adaptability. Extensibility refers to the ability to stretch current operations to surprising situations and adaptability refers to the ability to sustain operations into the future. We discuss ways to harness existing network optimization methods to study these forms of resilience and outline their limitations. We conclude by providing a research agenda that ensures the Networks community remains central to future advances in resilience while being pragmatic about the limitations of network optimization for achieving this task.

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“…As stated in the text, the proposed optimization model considers the assumption that the interdictions are in the shortest route routes of security units. For this purpose, many studies employ different approaches to improve defense systems in the literature [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Providing homeland security strategies against interdictions in the city transportation network: A case study in Turkey

Ayyıldız

Özçelik

Gencer

et al. 2023

Gazi University Journal of Science

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This paper defines a capacitated multiple-source multiple-sink shortest path problem and introduces its extension, called the capacitated multiple-source multiple-sink shortest path network interdiction problem (CMSSNIP). CMSSNIP examines the actions of attackers who attempt to maximize the total shortest path of network users trying to reach the crime locations for the aid process after causing an incident in certain regions to provide strategic information for the defense systems of the government. In this context, the exact mathematical model ensuring useful information about safe routes to network users is proposed. In this manner, to the best knowledge of authors, the CMSSNIP consisting of multiple-source nodes and multiple-sink nodes and considering capacity-demand relations between security units and crime locations is studied for the first time. Accordingly, a set of scenarios is considered based on the interdiction budget levels and the number of crime locations through a real case application to show the applicability of the model. Furthermore, computational experiments are performed to evaluate the model performance on different-sized networks. It is realized that especially the model provides resilient strategies versus interdictions in terms of obtaining the safe shortest paths at the operational level within seconds in the real case application.

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Protection-interdiction-restoration: Tri-level optimization for enhancing interdependent network resilience

Cited by 67 publications

References 62 publications

Adaptive algorithm for dependent infrastructure network restoration in an imperfect information sharing environment

Adaptive algorithm for dependent infrastructure network restoration in an imperfect information sharing environment

In search of network resilience: An optimization‐based view

Providing homeland security strategies against interdictions in the city transportation network: A case study in Turkey

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