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Optimization Model of Network-Level Pavement Maintenance Decision considering User Travel Time and Vehicle Fuel Consumption Costs

Auteur(s): ORCID
ORCID
ORCID

Médium: article de revue
Langue(s): anglais
Publié dans: Advances in Civil Engineering, , v. 2021
Page(s): 1-9
DOI: 10.1155/2021/4699838
Abstrait:

The maintenance management decisions of network-level asphalt pavements have long been a challenge to highway agencies, and a great amount of factors have been involved. In this study, a network-level optimization method was established by integrating the maintenance benefits into the zero-one programming optimization model. An optimized performance evaluation method of asphalt pavement was proposed which contains 11 different kinds of combinations. The benefit model quantifies the cost savings of user travel time and vehicle fuel consumption to the pavement condition index (PCI) and ride quality index (RQI), respectively. Based on the simplified evaluation method as well as the quantified maintenance benefit model, an optimization model was established by employing the zero-one programming. This optimization model aimed to maximize the improvements/price ratio of pavement maintenance for the whole pavement network. The calculation results present the optimal strategies of maintenance for every road section in the network. The applicability of the newly proposed model was validated by a case study. The methodology developed in this study helps to offer guidelines to highway agencies in managing and making decisions about network-level pavement maintenance.

Copyright: © 2021 Leilei Chen et al.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10628276
  • Publié(e) le:
    05.09.2021
  • Modifié(e) le:
    17.02.2022
 
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