A new methodology for optimisation under uncertainty

Project description

The mainstream research in combinatorial optimisation deals with well-defined problems where all problem parameters are  known in advance. In real-world scenarios, there is always some degree of uncertainty and variability in problem input. The existing techniques for handling such problems often deal with stability, sensitivity and robustness. Such methods are interesting from the theoretical viewpoint, but their application is usually quite limited due to their complexity.

A new approach to dealing with uncertainty, recently proposed in our preliminary research, is to produce a promising (probably non-optimal) solution based on parameters' estimates. That solution should keep its quality even if actual values of parameters would differ from the original estimates. The new concept of solution stability offers a powerful mathematical tool with a wider scope of problems that can be handled efficiently. Future work is needed to elaborate the new methodology and to explore its capabilities/limitations considering applications in various problem specific areas, such as scheduling, optimal assignment and resource allocation.

Entry requirements

Applications are invited from candidates with a minimum of a UK upper second class honours degree (2:1), and/ or a Master's degree in a relevant subject. We also recognise relevant industrial and academic experience.

How to apply

Formal applications for research degree study should be made online through the university's website. Please state clearly in the research information section of your application, the name of the PhD you wish to apply for is 'A new methodology for optimisation under uncertainty' as well as Dr Natasha Shakhlevich as your proposed supervisor. In the funding section, please state 'School of Computing Funded Studentships' as your sponsor.

If English is not your first language, you must provide evidence that you meet the University’s minimum English Language requirements.

We welcome scholarship applications from all suitably-qualified candidates, but UK black and minority ethnic (BME) researchers are currently under-represented in our Postgraduate Research community, and we would therefore particularly encourage applications from UK BME candidates.  All scholarships will be awarded on the basis of merit.

If you require any further information please contact the Graduate School Office
e: phd@engineering.leeds.ac.uk, t: +44 (0)113 343 8000.