讲座题目：Genetic Programming Hyper-Heuristics and Its Applications
讲座简介：This talk will introduce Genetic Programming Hyper-Heuristics (GPHH), which is a hybridised technique of evolutionary machine learning and optimisation, and is closely related to automated algorithm design. Unlike traditional optimisation techniques, GPHH optimises heuristics/algorithms that is more generalizable than solutions, and is much more effective for real-world problems, which usually has large problem size and dynamic environment. GPHH has achieved great success in a lot of complex optimisation problems such as job shop scheduling, vehicle routing, timetabling, etc. In this seminar, I will introduce the basics of GPHH, design issues and challenges, and some examples done in our Evolutionary Computation Research Group.
主讲人简介：Dr. Yi Mei (M’09-SM’18) is a Senior Lecturer at the School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand. His research interests include evolutionary scheduling and combinatorial optimisation, machine learning, genetic programming, and hyper-heuristics. He has more than 70 fully referred publications, including the top journals in EC and Operations Research such as IEEE TEVC, IEEE TCYB, Evolutionary Computation Journal, European Journal of Operational Research, ACM Transactions on Mathematical Software. He serves as a Vice-Chair of the IEEE CIS Emergent Technologies Technical Committee, and a member of Intelligent Systems Applications Technical Committee. He is an Editorial Board Member of International Journal of Bio-Inspired Computation, and a guest editor of a special issue of the Genetic Programming Evolvable Machine journal. He serves as a reviewer of over 30 international journals.