Max-Min Fair Restoration of Infrastructure Networks

Connectivity is one of the essential needs in today’s standards in many aspects of life, starting with personal relationships, education, and remote work and ending with the security and economy of countries. However, connectivity is susceptible to intentional and unintentional disruptions, leading to great impact on critical infrastructures. Hence, maintaining connectivity is a crucial task to sustain the continuous flow of life. The challenge is to find an optimal recovery plan to reconnect all demands as soon as possible after the disruptive event, ensuring fairness in the process of reallocating the remaining resources. In this paper, we present a post-disruption recovery framework for networked systems to optimize the recovery plan to reconnect the network demands as soon as possible. More specifically, we introduce an algorithmic approach using a mathematical programming model that optimally recovers the disrupted arcs of the network while ensuring the highest connectivity. The proposed approach considers both fairness and efficiency through finding the MMF (max-min fairness) resource allocation throughout the recovery process. The proposed approach is tested on a variety of benchmark networks under a set of disruption levels; then, the results are compared with the maximum-flow model.

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Publication Details

Journal
Mathematics
Published
2025-09-29
DOI
https://doi.org/10.3390/math13193112
Citations
1
Primary Topic
Infrastructure Resilience and Vulnerability Analysis
Type
article
Field-Weighted Citation Impact
0.95
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article

Max-Min Fair Restoration of Infrastructure Networks

Hamoud S. Bin Obaid, Mohammed Algafri, Yasser Almoghathawi
1 citations
Mathematics
Infrastructure Resilience and Vulnerability Analysis
0.95
article

Max-Min Fair Restoration of Infrastructure Networks

Hamoud S. Bin Obaid, Mohammed Algafri, Yasser Almoghathawi
article en
1 citations

Abstract

Connectivity is one of the essential needs in today’s standards in many aspects of life, starting with personal relationships, education, and remote work and ending with the security and economy of countries. However, connectivity is susceptible to intentional and unintentional disruptions, leading to great impact on critical infrastructures. Hence, maintaining connectivity is a crucial task to sustain the continuous flow of life. The challenge is to find an optimal recovery plan to reconnect all demands as soon as possible after the disruptive event, ensuring fairness in the process of reallocating the remaining resources. In this paper, we present a post-disruption recovery framework for networked systems to optimize the recovery plan to reconnect the network demands as soon as possible. More specifically, we introduce an algorithmic approach using a mathematical programming model that optimally recovers the disrupted arcs of the network while ensuring the highest connectivity. The proposed approach considers both fairness and efficiency through finding the MMF (max-min fairness) resource allocation throughout the recovery process. The proposed approach is tested on a variety of benchmark networks under a set of disruption levels; then, the results are compared with the maximum-flow model.

MathematicsVol. 13(19)
King Fahd University of Petroleum and Minerals (SA), King Saud University (SA), Saudi Aramco (Saudi Arabia) (SA)
Openalex Percentile: Top 21%
Infrastructure Resilience and Vulnerability Analysis
0.95
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