Operationalizing modular autonomous customised buses based on different demand prediction scenarios

This paper presents a novel framework for customised modular bus systems that leverages travel demand prediction and modular autonomous vehicles to optimise services proactively. The proposed framework addresses two prediction scenarios with different forward-looking operations: optimistic operation and pessimistic operation. A mixed integer...

“Measuring the Mix” of Policy Responses to COVID-19: Comparative Policy Analysis Using Topic Modelling

Although understanding initial responses to a crisis such as COVID-19 is important, existing research on the topic has not been systematically comparative. This study uses topic modeling to inductively analyze over 13,000 COVID-19 policies worldwide. This technique enables the COVID-19 policy mixes to be characterized and their cross-country...

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...