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Developing a fuzzy bi-objective programming and MCDM model for bridge maintenance strategy optimization.
Shojaei, Fereydoon; Naserabadi, Heidar Dashti; Taheri Amiri, Mohammad Javad.
Afiliação
  • Shojaei F; Department of Civil Engineering, Islamic Azad University, Qeshm Branch, Qeshm, Iran.
  • Naserabadi HD; Department of Civil Engineering, Islamic Azad University, Chaloos Branch, Chaloos, Iran. dashti@iauc.ac.ir.
  • Taheri Amiri MJ; Department of Civil Engineering, Higher Education Institute of Pardisan, Fereydunkenar, Mazandaran, Iran.
Sci Rep ; 14(1): 13336, 2024 Jun 10.
Article em En | MEDLINE | ID: mdl-38858432
ABSTRACT
Bridges serve as critical links in road networks, requiring continuous maintenance to ensure proper functionality throughout their lifespan. Given their pivotal role in the urban landscape, connecting various parts of a city, this research presents a multi-objective optimization model for the maintenance and repair of bridges in Babolsar, Iran. The model takes into account budget constraints and aims to minimize the total life cycle and user costs, encompassing traffic delays and vehicle expenses, while maximizing the reliability of the bridge network. Recognizing the inherent complexity of this problem, a multi-objective particle swarm optimization algorithm has been developed for an accurate solution. The study further conducts sensitivity analysis on the objective function concerning the available budget, evaluating key parameters such as hourly costs and the time value of vehicles. The results show that with an increase in the budget level, the number of repairs related to the most costly maintenance has significantly risen. In other words, as the budget expands, the model tends to favor repairs with higher costs because their impact on the bridge's performance is more substantial.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Irã País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Sci Rep Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Irã País de publicação: Reino Unido