Hyper-heuristics: A Survey of the State of the Art EK Burke, M Hyde, G Kendall, G Ochoa, E Ozcan, R Qu Journal of the Operational Research Society, 2013 | 2236* | 2013 |
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 | 1377 | 2019 |
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 | 757 | 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 (1), 55-89, 2009 | 625 | 2009 |
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 | 348* | 2010 |
Case-based heuristic selection for timetabling problems EK Burke, S Petrovic, R Qu Journal of Scheduling 9 (2), 115-132, 2006 | 325 | 2006 |
Personnel scheduling: Models and complexity P Brucker, R Qu, E Burke European Journal of Operational Research 210 (3), 467-473, 2010 | 283 | 2010 |
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 | 277 | 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 | 270 | 2008 |
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 | 226 | 2010 |
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 | 218 | 2016 |
A learning-guided multi-objective evolutionary algorithm for constrained portfolio optimization K Lwin, R Qu, G Kendall Applied Soft Computing 24, 757-772, 2014 | 209 | 2014 |
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 | 185 | 2009 |
Mean-VaR portfolio optimization: A nonparametric approach KT Lwin, R Qu, BL MacCarthy European Journal of Operational Research 260 (2), 751-766, 2017 | 183 | 2017 |
Hyper-Heuristics: Theory and Applications N Pillay, R Qu ISBN 978-3-319-96513-0; eBook ISBN 978-3, 2018 | 158 | 2018 |
A graph coloring constructive hyper-heuristic for examination timetabling problems NR Sabar, M Ayob, R Qu, G Kendall Applied Intelligence 37 (1), 1-11, 2011 | 152 | 2011 |
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 | 147 | 2010 |
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 | 146 | 2022 |
A scatter search methodology for the nurse rostering problem EK Burke, T Curtois, R Qu, GV Berghe Journal of the Operational Research Society 61 (11), 1667-1679, 2010 | 146 | 2010 |
A Honey-bee Mating Optimization Algorithm for Educational Timetabling Problems NR Sabar, M Ayob, G Kendall, R Qu European Journal of Operational Research 216 (3), 533-543, 2012 | 142 | 2012 |