Funding

Self-funded

Project code

SMAP7460423

Department

School of Mathematics and Physics

Start dates

October, February and April

Application deadline

Applications accepted all year round

Applications are invited for a self-funded, 3-year full-time or 6-year part time PhD project.

The PhD will be based in the School of Mathematics and Physics, LORA (Logistics, Operational Research and Analytics) Research Group, and will be supervised by Professor Djamila Ouelhadj.

The work on this project could involve:

  • Literature review on drone logistics.
  • Development of novel stochastic optimisation models and sim-optimisation meta-heuristic methods for the scheduling and the routing of drones to deliver medical products taking into account uncertainties on weather conditions and demand.
  • Performance evaluation of the proposed stochastic optimisation models and intelligent solution methods.
  • Evaluation of the economic, environmental, and social impacts of the use of drones for medical deliveries for the NHS to move medical supplies between three hospitals in Hampshire - Southampton General Hospital, Queen Alexandra Hospital in Portsmouth and St Mary’s Hospital on the Isle of Wight.

The project aims to use drones between medical centres across the Solent region for medical deliveries for the NHS to move medical supplies between three hospitals in Hampshire - Southampton General Hospital, Queen Alexandra Hospital in Portsmouth and St Mary’s Hospital on the Isle of Wight.

The project will develop and code a stochastic optimisation-simulation environment for optimising and evaluating multimodal supply chains involving land-to-UAV and UAV-to-land logistics interchanges, and the optimal scheduling of UAVs for deliveries and collections. The optimisation-simulation tool will be developed to aid logistics planners understand how multiple freight transport modes involving various land-to-UAV interfaces could be adopted into their existing operations, focusing on the NHS case study. This could include interfaces such as direct-to consignee (including land-and-deliver and in-flight drop), through micro-consolidation points to consignees or through dynamic drop-off points served by sustainable transport modes. The direct-to consignee (including land-and-deliver and in-flight drop), through micro-consolidation points to consignees or through dynamic drop-off points served by sustainable transport modes. The project will also develop the simulation and evaluation of the impacts of different potential drone-land and land-drone logistics operating scenarios. The models and algorithms developed are expected to be of sufficient scientific novelty and application worth that they will lead to articles published in leading operational research and transport scientific journals.

Entry requirements

You'll need a good first degree from an internationally recognised university or a Master’s degree in an appropriate subject. In exceptional cases, we may consider equivalent professional experience and/or qualifications. English language proficiency at a minimum of IELTS band 6.5 with no component score below 6.0.

Operational Research, programming skills (Java/C++, C#, etc.).

How to apply

We encourage you to contact Professor Djamila Ouelhadj (djamila.oulhadj@port.ac.uk) to discuss your interest before you apply, quoting the project code.

When you are ready to apply, please follow the 'Apply now' link on the Operational Research and Logistics PhD subject area page and select the link for the relevant intake. Make sure you submit a personal statement, proof of your degrees and grades, details of two referees, proof of your English language proficiency and an up-to-date CV. Our ‘How to Apply’ page offers further guidance on the PhD application process. 

When applying please quote project code:SMAP7460423.