Optimal prioritization of maintenance and rehabilitation (M&R) activities for pavement sections can enable significant time and cost-savings. In this study, we used the particle swarm optimization (PSO) method to achieve optimal prioritization of 135 pavement sections based on eight pavement condition parameters. The parameters included standard deviation (SD) for smoothness, rutting, deflections, cracking, pothole, bleeding, patching, and shoving. SD for smoothness, rutting, and deflections were inspected using instruments, while cracking, pothole, bleeding, patching, and shoving were surveyed visually. The PSO method was used to quickly calculate the synthetic pavement condition for each pavement section and then obtain the optimal prioritization of pavement sections. With this approach, pavement engineers are able to efficiently perform appropriate and timely M&R activities for pavement sections, according to their priority. This study provides an alternative solution to current approaches for prioritization of pavement sections.


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    Titel :

    Particle Swarm Optimization Method for Optimal Prioritization of Pavement Sections for Maintenance and Rehabilitation Activities


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    2013-07-31


    Format / Umfang :

    7 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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