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

If you are interested in hyper-heuristics, take a look at my publications in this area
http://bit.ly/efxLGg
Can ants play chess? Yes they can!
http://bit.ly/1yW3UhX

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

MISTA Conference: Almost There

Publication(s)

Scheduling English Football Fixtures: Consideration of Two Conflicting Objectives
RATE_LIMIT_EXCEEDED
Advanced Population Diversity Measures in Genetic Progaramming
RATE_LIMIT_EXCEEDED
A great deluge algorithm for a real-world examination timetabling problem
RATE_LIMIT_EXCEEDED
A Simulated Annealing Enhancement of the Best-Fit Heuristic for the Orthogonal Stock-Cutting Problem
RATE_LIMIT_EXCEEDED

Graham Kendall: Details of Requested Publication


Citation

Burke, E.K; Gendreau, M; Hyde, M; Kendall, G; McCollum, B; Ochoa, G; Parkes, A and Petrovic, S The Cross-domain Heuristic Search Challenge - An International Research Competition. In Proceedings of Learning and Intelligent Optmization (LION5), pages 631-634, Lecture Notes in Computer Science 6683, 2011.


Abstract

The first Cross-domain Heuristic Search Challenge (CHeSC 2011) seeks to bring together practitioners from operational research, computer science and arti cial intelligence who are interested in developing more generally applicable search methodologies. The challenge is to design a search algorithm that works well, not only across different instances of the same problem, but also across di erent problem domains. This article overviews the main features of this challenge.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.1007/978-3-642-25566-3_49 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/theoretical+computer+science/book/978-3-642-25565-6

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{bghkmopp2011, author = {E.K. Burke and M. Gendreau and M. Hyde and G. Kendall and B. McCollum and G. Ochoa and A. Parkes and S. Petrovic},
title = {The Cross-domain Heuristic Search Challenge - An International Research Competition},
booktitle = {Proceedings of Learning and Intelligent Optmization (LION5)},
year = {2011},
editor = {X. Yao and C. A. C. Coello},
volume = {6683},
series = {Lecture Notes in Computer Science},
pages = {631--634},
month = {Jan 17-21, 2011, Rome, Italy},
abstract = {The first Cross-domain Heuristic Search Challenge (CHeSC 2011) seeks to bring together practitioners from operational research, computer science and arti cial intelligence who are interested in developing more generally applicable search methodologies. The challenge is to design a search algorithm that works well, not only across different instances of the same problem, but also across di erent problem domains. This article overviews the main features of this challenge.},
doi = {10.1007/978-3-642-25566-3_49},
keywords = {hyper-heuristics, hyperheuristics, competition, meta-heuristics, metaheuristics},
owner = {gxk},
timestamp = {2010.12.09},
url = {http://www.springer.com/computer/theoretical+computer+science/book/978-3-642-25565-6},
webpdf = {http://www.graham-kendall.com/papers/bghkmopp2011.pdf} }