Abstract
This paper presents a computational framework for maintenance scheduling for road assets. This framework incorporates degradation and maintenance models along with optimization of maintenance strategies. Uncertainties inherit in the degradation process and effects of maintenance actions are addressed by considering model parameters as random variables and employing Monte Carlo simulation to estimate the future performance. The optimization involves the consideration of multiple objectives and the constraints satisfaction. The design variables are the type of maintenance actions and time of application. The objectives are the minimization of asset degradation and maintenance costs. The focus of experimental study is on slopes and retaining walls that are an integral part of many existing road networks. The obtained results demonstrate the validity and usefulness of the proposed framework. The presented framework can be generalized and applied to different types of infrastructure assets.
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