Abstract:
This study focuses on large-scale pavement maintenance and rehabilitation planning. Pavement agencies usually deal with large and diverse networks of thousands of pavement sections. The complexity of pavement maintenance and rehabilitation planning increases exponentially with the size of the network. Exact optimization methods designed for small-scale problems thus suffer from dimensionality, which significantly compromises the ability to solve such problems in a reasonable time period. Consequently, such problems should be approached from the technique of approximation. A method with the Lagrangian relaxation technique and a branch-and-cut algorithm is proposed for use as a decomposition scheme for pavement maintenance and rehabilitation planning problems when the size of the problem poses a major hurdle for its solution. The proposed approach first decomposes the network (original problem) into individual sections (subproblems) and then solves the subproblems separately. As shown in the case study, the proposed approach is able to solve problems with a practical size efficiently. More specifically, the results show that the proposed method can solve problems with a network of 1,000 sections within a reasonable time period and can yield a solution close to the optimal one.
