A new approach to multiyear maintenance and rehabilitation (M&R) optimization programming for pavement network management is discussed; the approach can be used to help highway agencies make strategic decisions in choosing the optimal investment for their pavement networks. The M&R treatments are standardized in terms of costs, benefits, and performance impacts on the existing pavements. Each standardized pavement treatment strategy, ranging from minor and routine maintenance to major rehabilitation or reconstruction, is defined by its effect and improvement on the existing pavement serviceability. The optimization model is a cost-effectiveness-based integer M&R programming on a year-by-year basis. The objective of the optimization system is to select the most effective M&R projects for each programming year. The optimization system can also be used to calculate the minimum budget requirements for maintaining a prescribed level of the pavement network performance or serviceability. In such a case, sensitivity analysis can be performed to evaluate the annual budget effect on individual pavement performance. The prediction of individual pavement deterioration is modeled as a time-related (nonhomogeneous) Markov transition process. The investigation described was primarily concerned with integration of the performance prediction model, the standardized M&R treatments, and the network optimization process. The principle and methodology developed can be applied to different levels of pavement network management. Finally, a sample application of the integrated pavement optimization model is demonstrated.


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    Titel :

    Integer Programming of Maintenance and Rehabilitation Treatments for Pavement Networks


    Weitere Titelangaben:

    Transportation Research Record: Journal of the Transportation Research Board


    Beteiligte:
    Li, Ningyuan (Autor:in) / Haas, Ralph (Autor:in) / Huot, Michel (Autor:in)


    Erscheinungsdatum :

    01.01.1998




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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