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

I have published some papers on timetabling.
http://bit.ly/hSGAhZ
If you are interested in hyper-heuristics, take a look at my publications in this area
http://bit.ly/efxLGg

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

Parsing Bibtex Authors: How I Do It

Publication(s)

Optimisation for Surface Mount Placement Machines
http://bit.ly/fbcxGc
The Entity-to-Algorithm Allocation Problem: Extending the Analysis
http://bit.ly/1yHLiyp
An investigation of a hyperheuristic genetic algorithm applied to a trainer scheduling problem
http://bit.ly/egxt0d
A Multiobjective Approach for UK Football Scheduling
http://bit.ly/fV4caa

Graham Kendall: Details of Requested Publication


Citation

Grobler, J; Engelbrecht, A.P; Kendall, G and Yadavalli, V.S.S Multi-method algorithms: Investigating the entity-to-algorithm allocation problem. In Proceedings of the 2013 IEEE Congress on Evolutionary Computation (CEC), pages 570-577, 2013.


Abstract

This paper investigates the algorithm selection problem, otherwise referred to as the entity-to-algorithm allocation problem, within the context of three recent multi-method algorithm frameworks. A population-based algorithm portfolio, a meta-hyper-heuristic and a bandit based operator selection method are evaluated under similar conditions on a diverse set of floating-point benchmark problems. The meta-hyper heuristic is shown to outperform the other two algorithms.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.1109/CEC.2013.6557619 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

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{geky2013, author = {J. Grobler and A.P. Engelbrecht and G. Kendall and V.S.S. Yadavalli},
title = {Multi-method algorithms: Investigating the entity-to-algorithm allocation problem},
booktitle = {Proceedings of the 2013 IEEE Congress on Evolutionary Computation (CEC)},
year = {2013},
pages = {570--577},
abstract = {This paper investigates the algorithm selection problem, otherwise referred to as the entity-to-algorithm allocation problem, within the context of three recent multi-method algorithm frameworks. A population-based algorithm portfolio, a meta-hyper-heuristic and a bandit based operator selection method are evaluated under similar conditions on a diverse set of floating-point benchmark problems. The meta-hyper heuristic is shown to outperform the other two algorithms.},
doi = {10.1109/CEC.2013.6557619},
keywords = {packing, cutting, nesting},
owner = {Graham},
timestamp = {2013.08.17},
webpdf = {http://www.graham-kendall.com/papers/geky2013.pdf} }