Abstract

The condition of pavement networks gradually deteriorates over years of use. Finding a suitable strategy to address this deterioration has become a key concern in pavement maintenance. Recently, pavement agencies have been facing uncertainties in maintenance and rehabilitation activities because of economic conditions and changes in climatic and traffic conditions, which complicate planning for strategy determination. Therefore, it is important for pavement agencies to be able to maximize pavement condition while considering uncertainty and minimizing the maintenance budget. In this paper, a pavement management model has been developed using a microscopic approach to overcome the complexity. The microscopic pavement management problem is formulated as an integer linear programming model, subject to budget constraints. The proposed microscopic model incorporates integer variables representing the pavement sections to be treated by the applicable maintenance and rehabilitation actions. Innovative approaches, cold paving techniques, are applied in the paper, offering substantial benefits in terms of environmental impact and resource efficiency. In the proposed model, distribution functions fitted to historical data are used to evaluate pavement condition performance. The objective of yielding optimum pavement conditions is achieved by considering uncertainty applied to a given pavement system. A case study was conducted by examining a network of eight pavement sections over a 5-year planning period. The model solutions are obtained by integrating activities and the epsilon-constraint method. In addition, the results of each solution are compared for the decision-maker. The results show that the proposed model is an attractive method for managing pavement maintenance programs at the network level.

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