Graham Kendall
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Professor Graham Kendall

Professor Graham Kendall is the Provost and CEO of The University of Nottingham Malaysia Campus (UNMC). He is also a Pro-Vice Chancellor of the University of Nottingham.

He is a Director of MyResearch Sdn Bhd, Crops for the Future Sdn Bhd. and Nottingham Green Technologies Sdn Bhd. He is a Fellow of the British Computer Society (FBCS) and a Fellow of the Operational Research Society (FORS).

He has published over 230 peer reviewed papers. He is an Associate Editor of 10 journals and the Editor-in-Chief of the IEEE Transactions of Computational Intelligence and AI in Games.

News

I am involved with a spin out company that specialises in Strategic Resource Planning
http://bit.ly/eTPZO2
The hunt for MH370
http://bit.ly/1DXRLbu

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

When Sports Rules Go Awry: How TheConversation led to a collaborative paper

Publication(s)

Youth Sports Leagues Scheduling
http://bit.ly/f1i7SE
Towards the 'Decathlon 'Challenge' of search heuristics
http://bit.ly/edfHGs
Solving the Fixed Channel Assignment Problem in Cellular Communications Using An Adaptive Local Search
http://bit.ly/icGZM5
Making Airline Schedules More Robust
http://bit.ly/hbGm4B

Graham Kendall: Details of Requested Publication


Citation

Sabar, N. R; Ayob, M and Kendall, G Solving Examination Timetabling Problems using Honey-bee Mating Optimization (ETP-HBMO). In Proceedings of the 4th Multidisciplinary International Conference on Scheduling: Theory and Applications (MISTA 2009), pages 399-408, Dublin, Ireland, 2009.


Abstract

Examination timetabling problems deal with assigning a set of exams into a limited number of timeslots, whilst satisfying a set of constraints. In this work, we propose ETP-HBMO (Examination Timetabling Problems-Honey-bee Mating Optimization) algorithm for solving examination timetabling problems. The honey-bee mating process is considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of real honey-bee mating. The mating process (i.e. generating a new solution) of the queen (current best solution) begins when the queen leaves the nest to perform a mating flight during which time the drones (trial solutions) follow the queen and mate with her. In this work, we test ETP-HBMO on Carterís un-capacitated benchmark examination timetable dataset and evaluate the performance using standard proximity costs. Results demonstrate that the performance of the Honey-bee Mating Optimization Algorithm is comparable with the results of other methodologies that have been reported in the literature over recent years. Indeed, ETP-HBMO outperformed other approaches on a few instances. This indicates that ETP-HBMO is effective in solving examination timetabling problems, and worthy of further research.


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Bibtex

@INPROCEEDINGS{sak2009a, author = {N. R. Sabar and M. Ayob and G. Kendall},
title = {Solving Examination Timetabling Problems using Honey-bee Mating Optimization (ETP-HBMO)},
booktitle = {Proceedings of the 4th Multidisciplinary International Conference on Scheduling: Theory and Applications (MISTA 2009)},
year = {2009},
pages = {399--408},
address = {Dublin, Ireland},
month = {10-12 Aug 2009},
abstract = {Examination timetabling problems deal with assigning a set of exams into a limited number of timeslots, whilst satisfying a set of constraints. In this work, we propose ETP-HBMO (Examination Timetabling Problems-Honey-bee Mating Optimization) algorithm for solving examination timetabling problems. The honey-bee mating process is considered as a typical swarm-based approach to optimization, in which the search algorithm is inspired by the process of real honey-bee mating. The mating process (i.e. generating a new solution) of the queen (current best solution) begins when the queen leaves the nest to perform a mating flight during which time the drones (trial solutions) follow the queen and mate with her. In this work, we test ETP-HBMO on Carterís un-capacitated benchmark examination timetable dataset and evaluate the performance using standard proximity costs. Results demonstrate that the performance of the Honey-bee Mating Optimization Algorithm is comparable with the results of other methodologies that have been reported in the literature over recent years. Indeed, ETP-HBMO outperformed other approaches on a few instances. This indicates that ETP-HBMO is effective in solving examination timetabling problems, and worthy of further research.},
keywords = {examination timetabling, heuristics, meta-heuristics, honey bee},
owner = {est},
timestamp = {2010.03.18},
webpdf = {http://www.graham-kendall.com/papers/sak2009a.pdf} }