Exploring the intersection of optimization, public transport, and urban sustainability.
Lancashire’s extension of the £1 evening and Sunday bus fare is welcome, but its long-term affordability should be tested through transparent mathematical modelling.
Develop an MSCA or Newton postdoctoral fellowship application in transport, logistics or operations research with Dr Yu Jiang at Lancaster University.
A new simulation-based framework searches for traffic-signal plans that balance efficiency, safety, and equity across private cars, buses, and bicycles.
A source-based review of selected public transport decisions, plans and implemented actions during Andy Burnham’s period in office.
How a novel bi-level optimization and Adaptive Large Neighborhood Search (ALNS) framework addresses the emerging challenge of online time slot booking in home healthcare routing.
A new bi-level optimisation and Bayesian framework identifies the full Pareto frontier of regulatory trade-offs between passengers, drivers, platforms, and government in coupled ridesourcing and taxi markets.
Fusing multisource transit data into a unified data pipeline that diagnoses service problems and prescribes evidence-based improvements through stochastic optimisation.
Introducing the Inverse-Square Rule: a mathematical breakthrough that transforms bus timetable optimization, achieving 36-45% cost reductions where traditional solvers fail.
TfL's proposed cuts to routes 19, 38, 259, and 349 reveal a critical gap between operational efficiency and network science. This is not just budgeting—it's a bi-level optimization challenge that demands rigorous mathematical modeling.