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

A Conversation article celebrating Pi
http://bit.ly/1DXuXbV
How are university examinations scheduled?
http://bit.ly/1z0pG4s

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Bibtax parser: Mashup no more

Publication(s)

The Limitations of Frequency Analysis for Dendritic Cell Population Modelling
RATE_LIMIT_EXCEEDED
Automated tile design for self-assembly conformations
RATE_LIMIT_EXCEEDED
Handling diversity in evolutionary multiobjective optimization
RATE_LIMIT_EXCEEDED
Evolving Bin Packing Heuristics with Genetic Programming
RATE_LIMIT_EXCEEDED

Graham Kendall: Details of Requested Publication


Citation

Dowsland, K. A; Herbert, E.A; G. Kendall, G. and Burke, E Using tree search bounds to enhance a genetic algorithm approach to two rectangle packing problems. European Journal of Operational Research, 168 (2): 390-402, 2006.


Abstract

A popular approach when using a genetic algorithm in the solution of constrained problems is to exploit problem specific information by representing individuals as ordered lists. A construction heuristic is then often used as a decoder to produce a solution from each ordering. In such a situation further information is often available in the form of bounds on the partial solutions. This paper uses two two-dimensional packing problems to illustrate how this information can be incorporated into the genetic operators to improve the overall performance of the search. Our objective is to use the packing problems as a vehicle for investigating a series of modifications of the genetic algorithm approach based on information from bounds on partial solutions.


pdf

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doi

The doi for this publication is 10.1016/j.ejor.2004.04.030 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


Journal Rankings


ISI Web of Knowledge Journal Citation Reports

The Web of Knowledge Journal Citation Reports (often known as ISI Impact Factors) help measure how often an article is cited. You can get an introduction to Journal Citation Reports here. Below I have provided the ISI impact factor for the jourrnal in which this article was published. For complete information I have shown the ISI ranking over a number of years, with the latest ranking highlighted.

2014 (2.358), 2013 (1.843), 2012 (2.038), 2011 (1.815), 2010 (2.158), 2009 (2.093), 2008 (1.627), 2007 (1.096), 2006 (0.918), 2005 (0.824), 2004 (0.828), 2003 (0.605), 2002 (0.553), 2001 (0.494), 2000 (0.490)

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

@ARTICLE{dhkb2006, author = {K. A. Dowsland and E.A. Herbert and G. Kendall, Graham and E. Burke},
title = {Using tree search bounds to enhance a genetic algorithm approach to two rectangle packing problems},
journal = {European Journal of Operational Research},
year = {2006},
volume = {168},
pages = {390--402},
number = {2},
month = {January 2006},
abstract = {A popular approach when using a genetic algorithm in the solution of constrained problems is to exploit problem specific information by representing individuals as ordered lists. A construction heuristic is then often used as a decoder to produce a solution from each ordering. In such a situation further information is often available in the form of bounds on the partial solutions. This paper uses two two-dimensional packing problems to illustrate how this information can be incorporated into the genetic operators to improve the overall performance of the search. Our objective is to use the packing problems as a vehicle for investigating a series of modifications of the genetic algorithm approach based on information from bounds on partial solutions.},
date-modified = {2007-01-16 16:10:05 +0000},
doi = {10.1016/j.ejor.2004.04.030},
issn = {0377-2217},
keywords = {Genetic Algorithms, Branch and Bound, Cutting, Packing},
webpdf = {http://www.graha-kendall.com/papers/dhkb2006.pdf} }