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

The hunt for MH370
http://bit.ly/1DXRLbu
If you are interested in hyper-heuristics, take a look at my publications in this area
http://bit.ly/efxLGg

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Claude Shannon, Edward Thorp, Roulette and Blackjack

Publication(s)

A New Dynamic Point Specification Approach to Optimise Surface Mount Placement Machine in Printed Circuit Board Assembly
RATE_LIMIT_EXCEEDED
A Survey of NP-Complete Puzzles
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Imperfect Evolutionary Systems
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The Cross-domain Heuristic Search Challenge - An International Research Competition
RATE_LIMIT_EXCEEDED

Graham Kendall: Details of Requested Publication


Citation

Burke, E.K and Kendall, G A New Approach to Packing Non-Convex Polygons Using the No Fit Polygon and Meta-Heuristic and Evolutionary Algorithms. In Proceedings of the 5th International Conference on Adapative Computing in Design and Manufacture (ACDM 2002), pages 193-204, Springer-Verlag, University of Exeter, UK, 16-18 April, 2002.


Abstract

Earlier work by the authors has presented a method for packing convex polygons, using a construction known as the no fit polygon. Although the method was shown to be successful, it could only deal with convex polygons. This paper addresses the issue by showing how a non-convex, no fit polygon algorithm can (and should) produce better quality solutions. We demonstrate the approach on two test problems that the authors have used in previous work. The new algorithm does, however, have an increased computational complexity. We tackle this by presenting an algorithm that allows the non-convex, no fit polygon to be approximated. This means that much more of the search space can be considered and computational results show that better quality solutions can be achieved, in less time than when using the full no fit polygon algorithm.


pdf

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doi

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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/engineering/mechanical+eng/book/978-1-85233-605-9

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Bibtex

@INPROCEEDINGS{bk2002a, author = {E.K. Burke and G. Kendall},
title = {A New Approach to Packing Non-Convex Polygons Using the No Fit Polygon and Meta-Heuristic and Evolutionary Algorithms},
booktitle = {Proceedings of the 5th International Conference on Adapative Computing in Design and Manufacture (ACDM 2002)},
year = {2002},
editor = {C.I. Parmee},
pages = {193--204},
address = {University of Exeter, UK, 16-18 April},
publisher = {Springer-Verlag},
abstract = {Earlier work by the authors has presented a method for packing convex polygons, using a construction known as the no fit polygon. Although the method was shown to be successful, it could only deal with convex polygons. This paper addresses the issue by showing how a non-convex, no fit polygon algorithm can (and should) produce better quality solutions. We demonstrate the approach on two test problems that the authors have used in previous work. The new algorithm does, however, have an increased computational complexity. We tackle this by presenting an algorithm that allows the non-convex, no fit polygon to be approximated. This means that much more of the search space can be considered and computational results show that better quality solutions can be achieved, in less time than when using the full no fit polygon algorithm.},
comment = {ISBN 1-85233-605-6},
keywords = {No Fit Polygon, NFP, Minkowski Sum, packing, nesting, heuristics, evolutinary algorithms, genetic algorithm, tabu search, simulated annealing, ant algorithm, memetic algorithm},
timestamp = {2007.03.29},
url = {http://www.springer.com/engineering/mechanical+eng/book/978-1-85233-605-9},
webpdf = {http://www.graham-kendall.com/papers/bk2002a.pdf} }