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 am the chair of the MISTA (Multidisciplinary International Conference on Scheduling: Theory and Applications)
http://bit.ly/hvZIaN
Can ants play chess? Yes they can!
http://bit.ly/1yW3UhX

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

3D Bin Packing, help Santa and share $10,000

Publication(s)

Ant Colonies Discover Knight's Tours
http://bit.ly/h0DqWF
Scheduling in sports: An annotated bibliography
http://bit.ly/eCfi42
The examination timetabling problem at Universiti Malaysia Pahang: Comparison of a constructive heuristic with an existing software solution
http://bit.ly/fqDS68
Hyperheuristics: A Tool for Rapid Prototyping in Scheduling and Optimisation
http://bit.ly/dVxwCs

Graham Kendall: Details of Requested Publication


Citation

Burke, E.K and Kendall, G Evaluation of Two Dimensional Bin Packing Problem using the No Fit Polygon. In Proceedings of the 26th International Conference on Computers and Industrial Engineering, pages 286-291, 15-17 December 1999, Melbourne, Australia, 1999.


Abstract

When employing evolutionary algorithms it is often the case that the evaluation function is the most computationally expensive part of the algorithm. Our evaluation function calculates the no fit polygon (NFP) for two polygons and then calculates the smallest convex hull for these two polygons. This process is repeated for each polygon. As the manipulation of polygons is computational expensive, the algorithm shows a bottleneck at this stage. However, many of the evaluations are simply reevaluating solutions that have already been evaluated. In order to use this information we use a cache which stores previous evaluations. By increasing the size of the cache size the speed of the algorithm is significantly increased. In addition the concept of a polygon type allows much better use to be made of the cache. In some circumstances, it may not be beneficial to use a cached evaluation. A reevaluation parameter is introduced which forces a complete reevaluation of a solution. We show that this parameter can be set to a small value so that we do not lose the advantages of the cache. These approaches are intuitive but are not often implemented, but they will become increasingly important as evolutionary algorithms are more widely used.


pdf

You can download the pdf of this publication from here


doi

This publication does not have a doi, so we cannot provide a link to the original source

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


Journal Rankings



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{bk1999b, author = {E.K. Burke and G. Kendall},
title = {Evaluation of Two Dimensional Bin Packing Problem using the No Fit Polygon},
booktitle = {Proceedings of the 26th International Conference on Computers and Industrial Engineering},
year = {1999},
pages = {286--291},
address = {15-17 December 1999, Melbourne, Australia},
abstract = {When employing evolutionary algorithms it is often the case that the evaluation function is the most computationally expensive part of the algorithm. Our evaluation function calculates the no fit polygon (NFP) for two polygons and then calculates the smallest convex hull for these two polygons. This process is repeated for each polygon. As the manipulation of polygons is computational expensive, the algorithm shows a bottleneck at this stage. However, many of the evaluations are simply reevaluating solutions that have already been evaluated. In order to use this information we use a cache which stores previous evaluations. By increasing the size of the cache size the speed of the algorithm is significantly increased. In addition the concept of a polygon type allows much better use to be made of the cache. In some circumstances, it may not be beneficial to use a cached evaluation. A reevaluation parameter is introduced which forces a complete reevaluation of a solution. We show that this parameter can be set to a small value so that we do not lose the advantages of the cache. These approaches are intuitive but are not often implemented, but they will become increasingly important as evolutionary algorithms are more widely used.},
issn = {0360-8352},
journal = {Computers \& Industrial Engineering},
keywords = {packing, nesting, evolutionary computation, no fit polygon, NFP, cache},
timestamp = {2007.03.29},
webpdf = {http://www.graham-kendall.com/papers/bk1999b.pdf} }