Optimization of Coordinated Flow Control and Skip-stopping Schemes for Urban Rail Stations Considering Platform Carrying Capacity

The platform carrying capacity of urban rail transit stations is limited and overcrowding of the platform will lead to serious safety risks for passengers and trains. It is significant to collaborate on the optimization of passenger flow strategy and skip-stopping scheme to alleviate traffic pressure and ensure platform safety. This study...

Dynamic Fleet Management for Autonomous Vehicles: Learning- and optimization-based strategies

Autonomous vehicles (AVs) have been heralded as the key to unlock a shared mobility future where transportation is more efficient, convenient, and cheaper. However, the AV utopia can only come to fruition if the majority of users trust that autonomous mobility-on-demand (AMoD) systems are on a par with owning a vehicle in terms of service...

A Study of Learning Search Approximation in Mixed Integer Branch and Bound: Node Selection in SCIP

In line with the growing trend of using machine learning to help solve combinatorial optimisation problems, one promising idea is to improve node selection within a mixed integer programming (MIP) branch-and-bound tree by using a learned policy. Previous work using imitation learning indicates the feasibility of acquiring a node selection policy...

Optimal non-zero Price Bids for EVs in Energy and Reserves Markets using Stochastic Optimization

In power systems, demand and supply always have to be balanced. This is becoming more challenging due to the sustained penetration of renewable energy sources. Because of the increasing amount of electrical vehicles (EVs), and the high capacity and flexibility of their charging process, EVs are a good candidate for providing balancing services...