Graham Kendall
Various Images

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

How are university examinations scheduled?
http://bit.ly/1z0pG4s
Does AI have a place in the board room?
http://bit.ly/1DXreuW

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

Bin Packing Made Easier?

Publication(s)

Document Zone Classification for Technical Document Images Using Artificial Neural Network and Support Vector Machines
http://bit.ly/1eUn8rs
Automating the Packing Heuristic Design Process with Genetic Programming
http://bit.ly/19OfB8C
An efficient guided local search approach for service network design problem with asset balancing
http://bit.ly/fY7uch
An ant algorithm hyperheuristic for the project presentation scheduling problem
http://bit.ly/gbUor9

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.


pdf

You can download the pdf of this publication from here


doi

This publication does not have a doi, so we cannot provide a link to the original source

What is a doi?: A doi (Document Object Identifier) is a unique identifier for sicientific papers (and occasionally other material). This provides direct access to the location where the original article is published using the URL http://dx.doi/org/xxxx (replacing xxx with the doi). See http://dx.doi.org/ for more information



URL

This pubication does not have a URL associated with it.

The URL is only provided if there is additional information that might be useful. For example, where the entry is a book chapter, the URL might link to the book itself.


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} }