Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Resilience-based mathematical model to restore disrupted road-bridge transportation networks
The transportation network resiliency plays a significant role in reducing the devastating impacts of a disaster. This paper develops a mathematical model to improve the resilience of road–bridge transportation networks in the recovery phase. The model consists of two objective functions. The first objective function minimises total recovery time, and the second one prioritises damaged bridges for restoration to increase network performance level in an early stage by maximising the skewness of the recovery trajectory. This paper considers disrupted bridges as repair projects and schedules a network of recovery tasks with precedence relationships to restore each bridge while considering resource constraints. Thus, it is similar to the resource–constraint multi-project scheduling problem. A genetic algorithm is applied to solve the model for a large-scale hypothetical road–bridge transport network, and the highway network of Shelby County, TN, the USA, following a seismic hazard. Different recovery task networks are considered to restore disrupted bridges. Three communities with rich, average and poor resources are compared to evaluate the impact of different community investment structures on the recovery process and network recovery time. The results show that the proposed restoration plan leads to achieving the best recovery trajectory and shortest total recovery time.
Resilience-based mathematical model to restore disrupted road-bridge transportation networks
The transportation network resiliency plays a significant role in reducing the devastating impacts of a disaster. This paper develops a mathematical model to improve the resilience of road–bridge transportation networks in the recovery phase. The model consists of two objective functions. The first objective function minimises total recovery time, and the second one prioritises damaged bridges for restoration to increase network performance level in an early stage by maximising the skewness of the recovery trajectory. This paper considers disrupted bridges as repair projects and schedules a network of recovery tasks with precedence relationships to restore each bridge while considering resource constraints. Thus, it is similar to the resource–constraint multi-project scheduling problem. A genetic algorithm is applied to solve the model for a large-scale hypothetical road–bridge transport network, and the highway network of Shelby County, TN, the USA, following a seismic hazard. Different recovery task networks are considered to restore disrupted bridges. Three communities with rich, average and poor resources are compared to evaluate the impact of different community investment structures on the recovery process and network recovery time. The results show that the proposed restoration plan leads to achieving the best recovery trajectory and shortest total recovery time.
Resilience-based mathematical model to restore disrupted road-bridge transportation networks
Somy, Samin (Autor:in) / Shafaei, Rasoul (Autor:in) / Ramezanian, Reza (Autor:in)
Structure and Infrastructure Engineering ; 18 ; 1334-1349
02.09.2022
16 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Resilience-based post-disaster recovery strategies for road-bridge networks
| Online Contents | 2017
Resilience-based post-disaster recovery strategies for road-bridge networks
| Taylor & Francis Verlag | 2017
| DOAJ | 2023