Reliability-based bridge design and life cycle management with Markov decision processes☆

Abstract A Markov Decision Process-based (MDP) modelling approach is used to identify optimal structural designs and their associated maintenance policies. This approach has the desirable attributes of capturing the dynamics of the coupled structural design/maintenance problem while yieldding a mathematical model that is computationally tractable. Implicit in the MDP is the computationally and theoretically usful choice of modelling the dynamics of structural performance and maintenance actions as two related but separate processes. Structural resistance deterioration due to corrosion and stochastic structural loading are modelled in the MDP as a “self-transition” process, that is, a process that models structural performance without maintenance intervention. A suite of maintenance actions and their associated costs constitute the core of the “decision effect” process. These two processes, made computationally operational through the development of self-transition and decision effect matrices, are then combined into a joint transition matrix, with which we can model the effects of maintenance actions on bridge performance and costs. Initial designs and their associated minimum expected, discounted lifetime costs are identified with the MDP for a two girder bridge.