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 blog occasionally, feel free to take a look.
http://bit.ly/hq6rMK
How are university examinations scheduled?
http://bit.ly/1z0pG4s

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

Learning Java, the first steps

Publication(s)

A Multiobjective Approach for UK Football Scheduling
http://bit.ly/fV4caa
Constructing Initial Neighbourhoods to Identify Critical Constraints
http://bit.ly/h3xfnd
A Game Theoretic Approach for Taxi Scheduling Problem with Street Hailing
http://bit.ly/1hBsesZ
On Nash equilibrium and evolutionarily stable states that are not characterised by the folk theorem
http://bit.ly/1J4KNC0

Graham Kendall: Details of Requested Publication


Citation

Burke, E.K; Hyde, M.R and Kendall, G A Squeaky Wheel Optimisation Methodology for Two Dimensional Strip Packing. Computers & Operations Research, 38 (7): 1035-1044, 2011.


Abstract

The two-dimensional strip packing problem occurs in industries such as metal, wood, glass, paper, and textiles. The problem involves cutting shapes from a larger stock sheet or roll of material, while minimising waste. This is a well studied problem for which many heuristic methodologies are available in the literature, ranging from the basic one-pass best-fit heuristic, to the state of the art Reactive GRASP and SVC(SubKP) iterative procedures. The contribution of this paper is to present a much simpler but equally competitive iterative packing methodology based on squeaky wheel optimisation. After each complete packing (iteration), a penalty is applied to pieces that directly decreased the solution quality. These penalties inform the packing in the next iteration, so that the offending pieces are packed earlier. This methodology is deterministic and very easy to implement, and can obtain some best results on benchmark instances from the literature.


pdf

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doi

The doi for this publication is 10.1016/j.cor.2010.10.005 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 (1.861), 2013 (1.718), 2012 (1.909), 2011 (1.720), 2010 (1.769), 2009 (2.116), 2008 (1.366), 2007 (1.147), 2006 (0.893), 2005 (0.746), 2004 (0.562), 2003 (0.486), 2002 (0.446), 2001 (0.375), 2000 (0.337)

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{bhk2011, author = {E.K. Burke and M.R. Hyde and G. Kendall},
title = {A Squeaky Wheel Optimisation Methodology for Two Dimensional Strip Packing},
journal = {Computers \& Operations Research},
year = {2011},
volume = {38},
pages = {1035--1044},
number = {7},
month = {July},
abstract = {The two-dimensional strip packing problem occurs in industries such as metal, wood, glass, paper, and textiles. The problem involves cutting shapes from a larger stock sheet or roll of material, while minimising waste. This is a well studied problem for which many heuristic methodologies are available in the literature, ranging from the basic one-pass best-fit heuristic, to the state of the art Reactive GRASP and SVC(SubKP) iterative procedures. The contribution of this paper is to present a much simpler but equally competitive iterative packing methodology based on squeaky wheel optimisation. After each complete packing (iteration), a penalty is applied to pieces that directly decreased the solution quality. These penalties inform the packing in the next iteration, so that the offending pieces are packed earlier. This methodology is deterministic and very easy to implement, and can obtain some best results on benchmark instances from the literature.},
doi = {10.1016/j.cor.2010.10.005},
issn = {0305-0548},
keywords = {cutting, packing, two-dimensional, strip packing, Cutting stock, Heuristics, Local search, Artificial intelligence},
owner = {gxk},
timestamp = {2010.12.03},
webpdf = {http://www.graham-kendall.com/papers/bhk2011.pdf} }