Graham Kendall
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Professor Graham Kendall

University of Nottingham, UK

I am a Professor of Computer Science at the University of Nottingham (UK). I am currently the Vice-Provost (Research and Knowledge Transfer) at our campus in Malaysia. I am a member of the Automated Scheduling, Optimisation and Planning (ASAP) Research Group. My interests include Operational Research, Evolutionary Computing, Scheduling (particularly sports scheduling), Cutting and Packing, Timetabling and Games (both games in the usual sense of the word as well as mathematical games such as the Iterated Prisoners Dilemma).

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News

I am the chair of the MISTA (Multidisciplinary International Conference on Scheduling: Theory and Applications)
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Publication

An Investigation of an Evolutionary Approach to the Opening of Go
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Publication

Evolving Collective Behavior in an Artificial Ecology
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Publication

Chapter 4: Genetic Algorithms
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Publication

Journals Rankings: Buyer Beware
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Graham Kendall: Details of Requested Publication


Citation

Allen, S. D; Burke, E.K and Kendall, G A hybrid placement strategy for the three-dimensional strip packing problem. European Journal of Operational Research, 209 (3): 219-227, 2011.


Abstract

This paper presents a hybrid placement strategy for the three-dimensional strip packing problem which involves packing a set of cuboids (‘boxes’) into a three-dimensional bin (parallelepiped) of fixed width and height but unconstrained length (the ‘container’). The goal is to pack all of the boxes into the container, minimising its resulting length. This problem has potential industry application in stock cutting (wood, polystyrene, etc. – minimising wastage) and also cargo loading, as well as other applications in areas such as multi-dimensional resource scheduling. In addition to the proposed strategy a number of test results on available literature benchmark problems are presented and analysed. The results of empirical testing of the algorithm show that it out-performs other methods from the literature, consistently in terms of speed and solution quality-producing 28 best known results from 35 test cases.


pdf

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doi

The doi for this publication is 10.1016/j.ejor.2010.09.023 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.

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

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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

@ARTICLE{abk2011, author = {S. D. Allen and E.K. Burke and G. Kendall},
title = {A hybrid placement strategy for the three-dimensional strip packing problem},
journal = {European Journal of Operational Research},
year = {2011},
volume = {209},
pages = {219--227},
number = {3},
abstract = {This paper presents a hybrid placement strategy for the three-dimensional strip packing problem which involves packing a set of cuboids (‘boxes’) into a three-dimensional bin (parallelepiped) of fixed width and height but unconstrained length (the ‘container’). The goal is to pack all of the boxes into the container, minimising its resulting length. This problem has potential industry application in stock cutting (wood, polystyrene, etc. – minimising wastage) and also cargo loading, as well as other applications in areas such as multi-dimensional resource scheduling. In addition to the proposed strategy a number of test results on available literature benchmark problems are presented and analysed. The results of empirical testing of the algorithm show that it out-performs other methods from the literature, consistently in terms of speed and solution quality-producing 28 best known results from 35 test cases.},
doi = {10.1016/j.ejor.2010.09.023},
keywords = {Cutting, Packing, Heuristics, Metaheuristics, meta-heuristics},
owner = {gxk},
timestamp = {2010.12.06},
webpdf = {http://www.graham-kendall.com/papers/abk2011.pdf} }