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 few papers on Sports Scheduling.
http://bit.ly/gVaUqT
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

How to get ants to solve a chess problem

Publication(s)

An Evolutionary Methodology for the Automated Design of Cellular Automaton-based Complex Systems
http://bit.ly/hlJNZh
Using an Evolutionary Algorithm for the Tuning of a Chess Evaluation Function Based on a Dynamic Boundary Strategy
http://bit.ly/hsgyZ8
A New Model and a Hyper-heuristic Approach for Two-dimensional Shelf Space Allocation
http://bit.ly/1h1JAhT
Collective Behavior and Kin Selection in Evolutionary IPD
http://bit.ly/if34nF

Graham Kendall: Details of Requested Publication


Citation

Grobler, J; Engelbrecht, A.P; Kendall, G and Yadavalli, V.S.S Alternative hyper-heuristic strategies for multi-method global optimization. In Proceedings of the 2010 IEEE Congress on Evolutionary Computation (CEC 2010), pages 826-833, 2010.


Abstract

The purpose of this paper is to investigate the use of meta-heuristics as low-level heuristics in a hyper-heuristic framework. A novel multi-method hyper-heuristic algorithm which makes use of a number of common meta-heuristics is presented. Algorithm performance is evaluated on a diverse set of real parameter benchmark problems and meaningful conclusions are drawn with respect to the selection of alternative low-level heuristics and the acceptance of the obtained solutions within the proposed multi-method meta-heuristic approach.


pdf

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doi

The doi for this publication is 10.1109/CEC.2010.5585980 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

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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

@INPROCEEDINGS{geky2010, author = {J. Grobler and A.P. Engelbrecht and G. Kendall and V.S.S. Yadavalli},
title = {Alternative hyper-heuristic strategies for multi-method global optimization},
booktitle = {Proceedings of the 2010 IEEE Congress on Evolutionary Computation (CEC 2010)},
year = {2010},
pages = {826--833},
month = {July 18-23 2010},
organization = {Barcelona, Spain},
abstract = {The purpose of this paper is to investigate the use of meta-heuristics as low-level heuristics in a hyper-heuristic framework. A novel multi-method hyper-heuristic algorithm which makes use of a number of common meta-heuristics is presented. Algorithm performance is evaluated on a diverse set of real parameter benchmark problems and meaningful conclusions are drawn with respect to the selection of alternative low-level heuristics and the acceptance of the obtained solutions within the proposed multi-method meta-heuristic approach.},
doi = {10.1109/CEC.2010.5585980},
keywords = {hyper-heuristics, optimization, heuristic programming, optimisation, hyperheuristics},
owner = {gxk},
timestamp = {2010.12.10},
webpdf = {http://www.graham-kendall.com/papers/geky2010.pdf} }