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 have published a number of papers on Cutting and Packing
http://bit.ly/dQPw7T
I am involved with a spin out company that specialises in Strategic Resource Planning
http://bit.ly/eTPZO2

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

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Bibtex: Display papers by a given author

Publication(s)

Sampling of Unique Structures and Behaviours in Genetic Programming
http://bit.ly/ehhZrr
Learning versus Evolution in Iterated Prisoner's Dilemma
http://bit.ly/eWgsgR
An Investigation of an Evolutionary Approach to the Opening of Go
http://bit.ly/dIVT5J
A Variable Neighborhood Descent Search Algorithm for Delay-Constrained Least-Cost Multicast Routing
http://bit.ly/h1puUB

Graham Kendall: Details of Requested Publication


Citation

Sabar, N. R; Ayob, M; Kendall, G and Qu, R A honey-bee mating optimization algorithm for educational timetabling problems. European Journal of Operational Research, 216 (3): 533-543, 2012.


Abstract

In this work, we propose a variant of the honey-bee mating optimization algorithm for solving educa tional timetabling problems. The honey-bee algorithm is a nature inspired algorithm which simulates the process of real honey-bees mating. The performance of the proposed algorithm is tested over two benchmark problems; exam (Carterís un-capacitated datasets) and course (Socha datasets) timetabling problems. We chose these two datasets as they have been widely studied in the literature and we would also like to evaluate our algorithm across two different, yet related, domains. Results demonstrate that the performance of the honey-bee mating optimization algorithm is comparable with the results of other approaches in the scientific literature. Indeed, the proposed approach obtains best results compared with other approaches on some instances, indicating that the honey-bee mating optimization algorithm is a promising approach in solving educational timetabling problems.


pdf

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doi

The doi for this publication is 10.1016/j.ejor.2011.08.006 You can link directly to the original paper, via the doi, from here

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


Journal Rankings


ISI Web of Knowledge Journal Citation Reports

The Web of Knowledge Journal Citation Reports (often known as ISI Impact Factors) help measure how often an article is cited. You can get an introduction to Journal Citation Reports here. Below I have provided the ISI impact factor for the jourrnal in which this article was published. For complete information I have shown the ISI ranking over a number of years, with the latest ranking highlighted.

2014 (2.358), 2013 (1.843), 2012 (2.038), 2011 (1.815), 2010 (2.158), 2009 (2.093), 2008 (1.627), 2007 (1.096), 2006 (0.918), 2005 (0.824), 2004 (0.828), 2003 (0.605), 2002 (0.553), 2001 (0.494), 2000 (0.490)

URL

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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

@ARTICLE{sakq2012, author = {N. R. Sabar and M. Ayob and G. Kendall and R. Qu},
title = {A honey-bee mating optimization algorithm for educational timetabling problems},
journal = {European Journal of Operational Research},
year = {2012},
volume = {216},
pages = {533--543},
number = {3},
abstract = {In this work, we propose a variant of the honey-bee mating optimization algorithm for solving educa tional timetabling problems. The honey-bee algorithm is a nature inspired algorithm which simulates the process of real honey-bees mating. The performance of the proposed algorithm is tested over two benchmark problems; exam (Carterís un-capacitated datasets) and course (Socha datasets) timetabling problems. We chose these two datasets as they have been widely studied in the literature and we would also like to evaluate our algorithm across two different, yet related, domains. Results demonstrate that the performance of the honey-bee mating optimization algorithm is comparable with the results of other approaches in the scientific literature. Indeed, the proposed approach obtains best results compared with other approaches on some instances, indicating that the honey-bee mating optimization algorithm is a promising approach in solving educational timetabling problems.},
doi = {10.1016/j.ejor.2011.08.006},
issn = {0377-2217},
keywords = {Honey Bee, Course Timetabling, Examination Timetabling, Exam, Carter, Socha, Meta-heuristics, population},
owner = {gxk},
timestamp = {2011.08.30},
webpdf = {http://www.graham-kendall.com/papers/sakq2012.pdf} }