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 involved with a spin out company that specialises in Strategic Resource Planning
http://bit.ly/eTPZO2
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

Using ELO ratings for match result prediction in association football

Publication(s)

Scheduling English Football Fixtures: Consideration of Two Conflicting Objectives
http://bit.ly/er0RSP
Sampling of Unique Structures and Behaviours in Genetic Programming
http://bit.ly/ehhZrr
Applying Evolutionary Algorithms and the No Fit Polygon to the Nesting Problem
http://bit.ly/fT4zDt
Handling diversity in evolutionary multiobjective optimization
http://bit.ly/hN8VPE

Graham Kendall: Details of Requested Publication


Citation

Burke, E.K and Kendall, G Applying Evolutionary Algorithms and the No Fit Polygon to the Nesting Problem. In Proceedings of the 1999 International Conference on Artificial Intelligence (IC-AI'99), pages 51-57, 28 June - 1 July, 1999, Monte Carlo Resort, Las Vegas, Nevada, USA, 1999.


Abstract

In previous work solutions for the nesting problem are produced using the No Fit Polygon (NFP), simulated annealing (SA) and a new evaluation method. It showed that SA could out perform hill climbing, thus suggesting that evolutionary approaches produce better solutions than a standard search algorithm. In this paper this work is developed. Genetic algorithms (GA) and tabu search (TS) are compared with the results already obtained with SA. The evaluation method is described, along with a description of the NFP. Computational results are given.


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Bibtex

@INPROCEEDINGS{bk1999d, author = {E.K. Burke and G. Kendall},
title = {Applying Evolutionary Algorithms and the No Fit Polygon to the Nesting Problem},
booktitle = {Proceedings of the 1999 International Conference on Artificial Intelligence (IC-AI'99)},
year = {1999},
pages = {51--57},
address = {28 June - 1 July, 1999, Monte Carlo Resort, Las Vegas, Nevada, USA},
abstract = {In previous work solutions for the nesting problem are produced using the No Fit Polygon (NFP), simulated annealing (SA) and a new evaluation method. It showed that SA could out perform hill climbing, thus suggesting that evolutionary approaches produce better solutions than a standard search algorithm. In this paper this work is developed. Genetic algorithms (GA) and tabu search (TS) are compared with the results already obtained with SA. The evaluation method is described, along with a description of the NFP. Computational results are given.},
comment = {ISBN 1-892512-16-5},
keywords = {packing, nesting, no fit polygon, evolutinary algorithm, genetic algoruthm, tabu search},
timestamp = {2007.03.29},
webpdf = {http://www.graham-kendall.com/papers/bk1999d.pdf} }