| A survey of deep learning-based object detection L Jiao, F Zhang, F Liu, S Yang, L Li, Z Feng, R Qu IEEE access 7, 128837-128868, 2019 | 1587 | 2019 |
| Hyper-heuristics: A survey of the state of the art EK Burke, M Gendreau, M Hyde, G Kendall, G Ochoa, E Özcan, R Qu Journal of the Operational Research Society 64 (12), 1695-1724, 2013 | 1553 | 2013 |
| A graph-based hyper-heuristic for educational timetabling problems EK Burke, B McCollum, A Meisels, S Petrovic, R Qu European Journal of Operational Research 176 (1), 177-192, 2007 | 761 | 2007 |
| A survey of search methodologies and automated system development for examination timetabling R Qu, EK Burke, B McCollum, LTG Merlot, SY Lee Journal of scheduling 12, 55-89, 2009 | 574 | 2009 |
| Case-based heuristic selection for timetabling problems EK Burke, S Petrovic, R Qu Journal of Scheduling 9, 115-132, 2006 | 329 | 2006 |
| Setting the research agenda in automated timetabling: The second international timetabling competition B McCollum, A Schaerf, B Paechter, P McMullan, R Lewis, AJ Parkes, ... Informs Journal on computing 22 (1), 120-130, 2010 | 312 | 2010 |
| Personnel scheduling: Models and complexity P Brucker, R Qu, E Burke European Journal of Operational Research 210 (3), 467-473, 2011 | 292 | 2011 |
| A hybrid model of integer programming and variable neighbourhood search for highly-constrained nurse rostering problems EK Burke, J Li, R Qu European Journal of Operational Research 203 (2), 484-493, 2010 | 287 | 2010 |
| A hybrid heuristic ordering and variable neighbourhood search for the nurse rostering problem EK Burke, T Curtois, G Post, R Qu, B Veltman European journal of operational research 188 (2), 330-341, 2008 | 278 | 2008 |
| Workforce scheduling and routing problems: literature survey and computational study JA Castillo-Salazar, D Landa-Silva, R Qu Annals of Operations Research 239, 39-67, 2016 | 240 | 2016 |
| Hybrid variable neighbourhood approaches to university exam timetabling EK Burke, AJ Eckersley, B McCollum, S Petrovic, R Qu European Journal of Operational Research 206 (1), 46-53, 2010 | 225 | 2010 |
| A learning-guided multi-objective evolutionary algorithm for constrained portfolio optimization K Lwin, R Qu, G Kendall Applied Soft Computing 24, 757-772, 2014 | 223 | 2014 |
| Mean-VaR portfolio optimization: A nonparametric approach KT Lwin, R Qu, BL MacCarthy European Journal of Operational Research 260 (2), 751-766, 2017 | 199 | 2017 |
| Hybridizations within a graph-based hyper-heuristic framework for university timetabling problems R Qu, EK Burke Journal of the Operational Research Society 60 (9), 1273-1285, 2009 | 189 | 2009 |
| An efficient federated distillation learning system for multitask time series classification H Xing, Z Xiao, R Qu, Z Zhu, B Zhao IEEE Transactions on Instrumentation and Measurement 71, 1-12, 2022 | 175 | 2022 |
| Hyper-heuristics: theory and applications N Pillay, R Qu Springer International Publishing, 2018 | 173 | 2018 |
| Apigenin ameliorates chronic mild stress-induced depressive behavior by inhibiting interleukin-1β production and NLRP3 inflammasome activation in the rat brain R Li, X Wang, T Qin, R Qu, S Ma Behavioural brain research 296, 318-325, 2016 | 173 | 2016 |
| A shift sequence based approach for nurse scheduling and a new benchmark dataset P Brucker, EK Burke, T Curtois, R Qu, G Vanden Berghe Journal of Heuristics 16, 559-573, 2010 | 155 | 2010 |
| A dynamic multiarmed bandit-gene expression programming hyper-heuristic for combinatorial optimization problems NR Sabar, M Ayob, G Kendall, R Qu IEEE transactions on cybernetics 45 (2), 217-228, 2014 | 151 | 2014 |
| A graph coloring constructive hyper-heuristic for examination timetabling problems NR Sabar, M Ayob, R Qu, G Kendall Applied Intelligence 37, 1-11, 2012 | 150 | 2012 |
Edmund Kieran BurkeBangor UniversityPatvirtintas el. paštas bangor.ac.uk