Our Blog
Exploring the intersection of optimization, public transport, and urban sustainability.
Featured Posts
Routing and Scheduling in Home Health Care: The Power of Online Time Slot Selection
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.
Who Wins When Uber and Taxis Compete? The Case for Pareto-Optimal Regulation
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.
OptimalTransit Hub: An End-to-End Analytics and Optimisation Platform
Fusing multisource transit data into a unified data pipeline that diagnoses service problems and prescribes evidence-based improvements through stochastic optimisation.
The Inverse-Square Rule: Smarter Algorithms, Better Buses
Introducing the Inverse-Square Rule: a mathematical breakthrough that transforms bus timetable optimization, achieving 36-45% cost reductions where traditional solvers fail.
Passengers Matter: Why Transit Assignment is the Key to TfL’s Route Changes
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.
Featured Posts
Routing and Scheduling in Home Health Care: The Power of Online Time Slot Selection
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.
Who Wins When Uber and Taxis Compete? The Case for Pareto-Optimal Regulation
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.
OptimalTransit Hub: An End-to-End Analytics and Optimisation Platform
Fusing multisource transit data into a unified data pipeline that diagnoses service problems and prescribes evidence-based improvements through stochastic optimisation.
The Inverse-Square Rule: Smarter Algorithms, Better Buses
Introducing the Inverse-Square Rule: a mathematical breakthrough that transforms bus timetable optimization, achieving 36-45% cost reductions where traditional solvers fail.
Passengers Matter: Why Transit Assignment is the Key to TfL’s Route Changes
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.