d. Many of the infrastructure sectors that are considered to be crucial by the Department of Homeland Security include networked systems (physical and temporal) that function to move some commodity like electricity, people, or even communication from one location of importance to another. The costs associated with these flows make up the price of the network’s normal functionality. These networks have limited capacities, which cause the marginal cost of a unit of flow across an edge to increase as congestion builds. In order to limit the expense of a network’s normal demand we aim to increase the resilience of the system and specifically the resilience of the arc capacities. Divisions of critical infrastructure have faced difficulties in recent years as inadequate resources have been available for needed upgrades and repairs. Without being able to determine future factors that cause damage both minor and extreme to the networks, officials must decide how to best allocate the limited funds now so that these essential systems can withstand the heavy weight of society’s reliance. We model these resource allocation decisions using a two-stage stochastic program (SP) for the purpose of network protection. Starting with a general form for a basic two-stage SP, wemore »
Design of Risk-Sharing Mechanism Related to Extreme Events
The occurrence of extreme events, either natural or man-made, puts stress on both the physical infrastructure, causing damages and failures, and the financial system. The following recovery process requires a large amount of resources from financial agents, such as insurance companies. If the demand for funds overpasses their capacity, these financial agents cannot fulfill their obligations, thus defaulting, without being able to deliver the requested funds. However, agents can share risk among each other, according to specific agreements. Our goal is to investigate the relationship between these agreements and the overall response of the physical/financial systems to extreme events and to identify the optimal set of agreements, according to some risk-based metrics. We model the system as a directed and weighted graph, where nodes represent financial agents and links agreements among these. Each node faces an external demand of funds coming from the physical assets, modeled as a random variable, that can be transferred to other nodes, via the directed edges. For a given probabilistic model of demands and structure of the graph, we evaluate metrics such as the expected number of defaults, and we identify the graph configuration which optimizes the metric. The identified graph suggests to the agents a set more »
- Award ID(s):
- Publication Date:
- NSF-PAR ID:
- Journal Name:
- Proc. of the 19th Working Conference of the IFIP Working Group 7.5 on Reliability and Optimization of Structural Systems, ETH Zurich, Zentrum, June 26-29, 2018.
- Page Range or eLocation-ID:
- Sponsoring Org:
- National Science Foundation
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