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 the chair of the MISTA (Multidisciplinary International Conference on Scheduling: Theory and Applications)
http://bit.ly/hvZIaN
Can ants play chess? Yes they can!
http://bit.ly/1yW3UhX

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

Wildcards and Carriage Returns in Word

Publication(s)

An Investigation of a Tabu Search Based Hyper-Heuristic for Examination Timetabling
http://bit.ly/1mlqRSh
Document Zone Classification for Technical Document Images Using Artificial Neural Network and Support Vector Machines
http://bit.ly/1eUn8rs
Real-time Scheduling for Multi Headed Placement Machine
http://bit.ly/eVWnGn
Searching the Hyper-heuristic Design Space
http://bit.ly/1sD4RoY

Graham Kendall: Details of Requested Publication


Citation

Gibbs, J; Kendall, G and Özcan, E Scheduling English Football Fixtures over the Holiday Period Using Hyper-heuristics. In Proceedings of Problem Parallel Solving from Nature (PPSN XI), Sep 2010, pages 496-505, Springer Berlin / Heidelberg, Lecture Notes in Computer Science 6238, 2011.


Abstract

One of the annual issues that has to be addressed in English football is producing a fixture schedule for the holiday periods that reduces the travel distance for the fans and players. This problem can be seen as a minimisation problem which must abide to the constraints set by the Football Association. In this study, the performance of selection hyper-heuristics is investigated as a solution methodology. Hyper-heuristics aim to automate the process of selecting and combining simpler heuristics to solve computational search problems. A selection hyper-heuristic stores a single candidate solution in memory and iteratively applies selected low level heuristics to improve it. The results show that the learning hyper-heuristics outperform some previously proposed approaches and solutions published by the Football Association.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.1007/978-3-642-15844-5_50 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



URL

The URL for additional information is http://www.springer.com/computer/bioinformatics/book/978-3-642-15843-8

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{gko2011, author = {J. Gibbs and G. Kendall and E. \"{O}zcan},
title = {Scheduling English Football Fixtures over the Holiday Period Using Hyper-heuristics},
booktitle = {Proceedings of Problem Parallel Solving from Nature (PPSN XI), Sep 2010},
year = {2011},
editor = {R. Schaefer and C. Cotta and J Kolodziej and G.Rudolph},
volume = {6238},
series = {Lecture Notes in Computer Science},
pages = {496--505},
month = {11-15 September 2010},
publisher = {Springer Berlin / Heidelberg},
abstract = {One of the annual issues that has to be addressed in English football is producing a fixture schedule for the holiday periods that reduces the travel distance for the fans and players. This problem can be seen as a minimisation problem which must abide to the constraints set by the Football Association. In this study, the performance of selection hyper-heuristics is investigated as a solution methodology. Hyper-heuristics aim to automate the process of selecting and combining simpler heuristics to solve computational search problems. A selection hyper-heuristic stores a single candidate solution in memory and iteratively applies selected low level heuristics to improve it. The results show that the learning hyper-heuristics outperform some previously proposed approaches and solutions published by the Football Association.},
doi = {10.1007/978-3-642-15844-5_50},
keywords = {hyper-heuristics, sport, soccer, football, scheduling},
owner = {gxk},
timestamp = {2010.12.09},
url = {http://www.springer.com/computer/bioinformatics/book/978-3-642-15843-8},
webpdf = {http://www.graham-kendall.com/papers/gko2011.pdf} }