Recovery Plans for Synchromodal Transport Systems

Abstract

In this research, we provide an algorithm for dynamically adjusting a transport plan in the case of disturbances in a synchromodal transport system. Recently several research projects have introduced decision support tools to solve planning problems in the synchromodal network that can handle the vast amount of information, but recovery planning in case of disturbances is underrepresented. Our aim is to explore when adjustments to the plan are necessary in case of a disturbance in a network, maximizing expected revenue. Disturbances are categorized right upon their occurrence and the category is updated as new information becomes known. We model the progress of a disturbance by a Markov Chain and define a Markov Decision Process to obtain a recovery strategy. We focus on a single chain of freight transport, employing different modes, and provide solutions for reacting to unplanned disturbances. A case study from industry provides validation of this algorithm.