Primary supervisor
Edward LamResearch area
OptimisationTransport and logistics businesses today use a large fleet of trucks and vans to deliver packages widely across a city. Deciding which package should be loaded on to which vehicle and deciding which package should be prioritised are surprisingly difficult computational tasks. State-of-the-art high-performance algorithms are used to calculate routes for the vehicles in order to minimise costs and maximise efficiency.
This project considers a future transport system that combines flying drones with conventional ground-level trucks. In this system, as a truck approaches a customer, a drone is launched to deliver a package, meanwhile the truck moves to the next customer. After delivering the package, the drone must rendezvous with the truck. Computing the location and time of these connections remains an unsolved computational challenge. This project will create new algorithms for calculating cost-effective and time-efficient routes for the trucks and drones, while ensuring that the drones always have a truck to land on.
Required knowledge
This project would suit a mathematics or computer science student with a background in combinatorial optimisation, operations research or mixed integer linear programming. An ability to code in C, C++ or Rust is also necessary. Candidates with experience or interest in column generation, cutting planes, polyhedral geometry and graph theory are especially invited to apply. A fully-funded scholarship for course fees, living allowance (food, rent, entertainment, etc.) and international conference travel may be available.