Seminario - Recent Advances in Selection Hyper-heuristics
Venerdì 17 dicembre alle ore 15:30 il prof. Ender Ozcan, Associate Professor of Computer Science and Operational Research, School of Computer Science, University of Nottingham, UK, terrà un seminario online dal titolo **"Recent Advances in Selection Hyper-heuristics"**.
Il seminario, della durata di 1h, si svolgerà tramite piattaforma Teams ed è aperto a tutti gli interessati utilizzando il link sotto riportato.
*Abstract*
A hyper-heuristic can be defined as a high-level automated search methodology which explores the search space formed by low-level heuristics (neighbourhood or move operators, or metaheuristics) or heuristic components, to solve computationally hard problems. There
are two main types of hyper-heuristics: methodologies to generate heuristics and to select heuristics. This talk will focus on the class of selection hyper-heuristics that control a set of low-level heuristics during an iterative search process. Based on a common
framework, a selection hyper-heuristic applies a chosen low-level heuristic to the current solution at each step of a search, before deciding whether to accept or reject the newly created solution. We will provide a brief review of selection hyper-heuristics, capturing
the recent advances in this rapidly growing area of research and cover some case studies carried out in our research group.
*Biography*
Dr Özcan is an internationally-leading scientist in computational optimisation for intelligent decision support, underpinned by
hyper-heuristics/metaheuristics combined with data science, tackling challenging real-world problems. His pioneering work at the interface
of Computer Science, Artificial Intelligence and Operational Research has been extensively exploited and extended by other researchers,
resulting in high number of citations, plenaries/keynotes at conferences, invited talks/guest lectures and tutorials. Currently,
40% of his journal research outputs are within top 10% of the highly-cited papers in Computer Science (ESSI), and he is ranked
within the World?s top 2% scientists in Artificial Intelligence based on the recent study by Elsevier BV and Stanford University. He served
as an Executive Committee member for the LANCS initiative. He was the Deputy Director of the EPSRC's National Taught Course Centre in
Operational Research (NATCOR). Dr Özcan has over 150 refereed publications at reputable venues. He is a Senior Member of IEEE and an
elected member of the EPSRC College. Dr Özcan contributed and has been contribut?ng to the funded projects worth £14.3M in total to date as
principal investigator and co-investigator/named researchers, supported by various funding bodies, including the EPSRC, European
Commission, The Royal Society, TSB, and TUBITAK. Dr Özcan is a co-founder and co-chair of the EURO Working Group on Data Science
Meets Optimisation. He is Associate Editor of the Journal of Scheduling and International Journal of Applied Metaheuristic
Computing, and on the Editorial Advisory Board of the International Journal of Intelligent Computing and Cybernetics. He is Steering
Committee member and Executive Officer of the International Conference Series on the Practice and Theory of Automated Timetabling (PATAT).