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I (have) taught all or parts of the following modules:
I have successfully supervised or supported the supervision of several undergraduate and postgraduate projects in a variety of topics including heuristic methods and mathematical programming techniques for combinatorial optimisation problems. Some of the projects I have supervised have won the department prize for the most outstanding project of the year, some have led to publications and some are client-based projects.
See the list of projects that I have supervised or externally supervised here
Title: Hyper/Meta-heuristics for Combinatorial Optimisation Problems
Description: Meta-heuristics, such as genetic algorithms, simulated annealing and tabu search, are now an established tool for solving hard optimisation problems. A more recent concept is that of "hyper-heuristics", which are algorithms that seek to automate the process of selecting and/or generating (meta-)heuristics. Whereas meta-heuristics draw on Operational Research and Artificial Intelligence, hyper-heuristics draw on Machine Learning and Data Science. The main aim of this research project is to develop high quality meta- and/or hyper-heuristics for combinatorial optimisation problems. The problems under consideration can include (but are not limited to) routing, cutting, packing, placement, graph theoretical, timetabling and scheduling problems.
Applicants for this topic should have reasonable mathematical ability, a general interest in optimisation, and strong programming skills. Experience with LaTeX/git is also desirable, but is not essential as training can be given.
Since being appointed as a lecturer in the Department of Management Science at Lancaster University, I have undertaken a number of administration duties for the department.
If you want a reference then please provide me with the following details: