| description abstract | Pavements often are divided into short segments for data collection, analysis, and management in practice. However, in pavement maintenance and rehabilitation (M&R) planning, it is impractical and uneconomical to create M&R projects based on such short segments. Road agencies generally group consecutive pavement segments to facilitate larger projects. However, the grouping is not easy, especially for large networks, and inappropriate grouping might result in resource wastage and ineffective M&R plans. Thus, an advanced and effective grouping method is required for decision makers when making M&R plans. This study focused on grouping consecutive pavement segments in the context of network-level multiyear M&R planning and developed a multiobjective optimization (MOO)-based grouping method. The MOO model was established with three conflicting objectives: minimizing the total agency costs, minimizing the total road user costs, and maximizing the network pavement performance, subject to the constraints of annual budgets, individual and network pavement performance, and the minimal and maximal length required for a M&R project. The proposed MOO-based grouping method was tested and compared with the clustering-based grouping method and no grouping method using a real road network–based case study in the context of a 5-year pavement M&R plan. The results showed that the proposed method can help decision-makers effectively conduct segment grouping and generate cost-effective solutions when conducting pavement M&R planning at the multiyear network level. | |
