Weiyao Meng is a Teaching Associate in the School of Computer Science at the University of Nottingham. Her PhD focuses on the automated design of local search algorithms with machine learning and data mining techniques, taking the vehicle routing problems with time windows as a testbed. She received her MSc from King's College London, UK and graduated from Shandong Normal University, China.
She was a Research Assistant in the Amicable Charging (AMiCC) research project, delivering eco-friendly wireless charging solutions for electric vehicles, focusing on optimizing the charging infrastructure.
She recently completed a KTP project as a KTP Associate to develop and deploy novel and advanced hyper-heuristics-based routing technologies for haulage markets.
She has also served as a reviewer for leading journals including IEEE Transactions on Evolutionary Computation, Engineering Applications of Artificial Intelligence, and Journal of the Operational Research Society.
Modules conveyed: Fundamentals of Artificial Intelligence and support the modules (as co-convenor)
Modules supported: Mathematics for Computer Scientists, Programming and Algorithms, Systems and Architecture, Computer Fundamentals, Operating Systems & Concurrency, Developing Maintainable Software, Simulation and Optimisation for Decision Support, and Data Modelling and Analysis.
Weiyao's PhD mainly investigates the automated design of local search algorithms for vehicle routing problems with machine learning techniques. Her main research interests focus on… read more
Weiyao's PhD mainly investigates the automated design of local search algorithms for vehicle routing problems with machine learning techniques. Her main research interests focus on heuristic,hyper-heuristic and metaheuristic optimisation techniques supported by machine learning for real-world optimization and decision support.
Keywords: Automated Algorithm Design, Hyper-heuristics, Vehicle Routing, and Combinatorial Optimization.