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
I have published a number of papers on Cutting and Packing
http://bit.ly/dQPw7T

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Horse Race Prediction with Neural Networks

Publication(s)

Scheduling TV Commercials: Models and Solution Methodologies
http://bit.ly/idSBCA
A great deluge algorithm for a real-world examination timetabling problem
http://bit.ly/1xCdCSx
The evolution of blackjack strategies
http://bit.ly/gdKjUc
Document Zone Classification for Technical Document Images Using Artificial Neural Network and Support Vector Machines
http://bit.ly/1eUn8rs

Graham Kendall: Details of Requested Publication


Citation

Grobler, J; Engelbrecht, A.P; Kendall, G and Yadavalli, V.S.S The Entity-to-Algorithm Allocation Problem: Extending the Analysis. In Proceedings of the 2014 Symposium Series on Computational Intelligence (IEEE SSCI 2014), 2014.


Abstract

This paper extends the investigation into the algorithm selection problem in hyper-heuristics, otherwise referred to as the entity-to-algorithm allocation problem, introduced by Grobler et al. [1]. Two newly developed population-based portfolio algorithms (the evolutionary algorithm based on selfadaptive learning population search techniques (EEA-SLPS) [2] and the Multi-EA algorithm [3]) are compared to two metahyper-heuristic algorithms. The algorithms are evaluated under similar conditions and the same set of constituent algorithms on a diverse set of floating-point benchmark problems. One of the meta-hyper-heuristics are shown to outperform the other algorithms, with EEA-SLPS coming in a close second.


pdf

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doi

The doi for this publication is 10.1109/CIEL.2014.7015744 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{geky2014a, author = {J. Grobler and A.P. Engelbrecht and G. Kendall and V.S.S. Yadavalli},
title = {The Entity-to-Algorithm Allocation Problem: Extending the Analysis},
booktitle = {Proceedings of the 2014 Symposium Series on Computational Intelligence (IEEE SSCI 2014)},
year = {2014},
month = {9-12 Dec 2014},
organization = {Orlando, Florida},
abstract = {This paper extends the investigation into the algorithm selection problem in hyper-heuristics, otherwise referred to as the entity-to-algorithm allocation problem, introduced by Grobler et al. [1]. Two newly developed population-based portfolio algorithms (the evolutionary algorithm based on selfadaptive learning population search techniques (EEA-SLPS) [2] and the Multi-EA algorithm [3]) are compared to two metahyper-heuristic algorithms. The algorithms are evaluated under similar conditions and the same set of constituent algorithms on a diverse set of floating-point benchmark problems. One of the meta-hyper-heuristics are shown to outperform the other algorithms, with EEA-SLPS coming in a close second.},
doi = {10.1109/CIEL.2014.7015744},
owner = {gxk},
timestamp = {2010.12.10},
webpdf = {http://www.graham-kendall.com/papers/geky2014a.pdf} }