PhD: Coordinated Control for Predictive Synchromodality
Large-scale transport and logistics systems are key in satisfying societies' demand for more reliable and efficient delivery of goods. Real-time information availability via huge numbers of sensors and the widespread availability of computation and communication power enable the development of new, real-time control and coordination strategies. Synchromodality is a promising concept that explicitly aims at benefitting from these developments to optimise transport logistics.
In this project, your goal is to propose and evaluate new methods that properly deal with the inherent complexity of synchromodal freight transport systems. You will hereby consider as a starting point the existence of multiple controllers / decision makers. Information is assumed not to be available at a central location but instead distributed over a number of different locations, and this information can include uncertainty. Moreover, decisions are not made by a single decision maker, but by multiple decision makers. Interactions among these decision makers in terms of exchange of different types of information lead to various ways of negotiation and cooperation strategies. Considering the decision makers all together, you will propose a distributed optimisation problem setting, in which multiple optimisation problems need to be solved, taking into account interconnecting constraints and objectives. The main challenge then becomes how to solve this distributed problem, taking into account information sharing constraints and degrees of uncertainty. You will work with the industrial users in the project on realistic case studies in order to assess the potential of different coordination strategies.
This job comes from a partnership with Science Magazine and