Technical Papers
Dec 30, 2022

Resource Allocation Framework for Optimizing Long-Term Infrastructure Network Resilience

Publication: Journal of Infrastructure Systems
Volume 29, Issue 1

Abstract

With the increase in frequency and severity of extreme weather events, it is essential to incorporate the resilience of infrastructure networks into the decision-making process of resource allocation for maintenance planning. Considering that infrastructure systems are interdependent in nature, the impact of both extreme events and maintenance treatments on infrastructure resilience could be further amplified. Consequently, infrastructure interdependencies should be considered when analyzing the impact of extreme events and maintenance treatments. Additionally, uncertainties (such as uncertainties associated with the occurrence of extreme events and maintenance treatment effects) should also be into consideration. This paper proposes a resource allocation framework that incorporates these factors to optimize long-term resilience of infrastructure networks. The proposed framework capitalizes on integrating agent-based modeling with a double deep Q-network model to support decision-making in resource allocations; it allows infrastructure management agencies to maximize the long-term resilience of infrastructure networks while keeping their physical condition at an acceptable level. The results obtained from the case study show that the proposed framework is effective and can be customized to various local conditions.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request. These include the expanded algorithm used in the case study and the location data of the infrastructure network in the case study.

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Go to Journal of Infrastructure Systems
Journal of Infrastructure Systems
Volume 29Issue 1March 2023

History

Received: Sep 21, 2021
Accepted: Nov 9, 2022
Published online: Dec 30, 2022
Published in print: Mar 1, 2023
Discussion open until: May 30, 2023

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Postdoctoral Fellow, Dept. of Civil, Architectural and Environmental Engineering, Univ. of Texas at Austin, Austin, TX 78712 (corresponding author). ORCID: https://orcid.org/0000-0001-6525-849X. Email: [email protected]
Research Associate, Center for Transportation Research, Univ. of Texas at Austin, Austin, TX 78712. ORCID: https://orcid.org/0000-0001-9104-0179
Zhanmin Zhang, A.M.ASCE
Clyde E. Lee Endowed Professor, Dept. of Civil, Architectural and Environmental Engineering, Univ. of Texas at Austin, Austin, TX 78712.

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