Graham Kendall
Various Images

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).

News

I have published a number of papers on Cutting and Packing
http://bit.ly/dQPw7T
What do we spend so much in supermarkets?
http://bit.ly/1yW6If7

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 Game Theoretic Approach for Taxi Scheduling Problem with Street Hailing
http://bit.ly/1hBsesZ
A Hybrid Differential Evolution Algorithm - Game Theory for the Berth Allocation Problem
http://bit.ly/1OjS0k9
An efficient and robust approach to generate high quality solutions for the Traveling Tournament Problem.
http://bit.ly/fCqNU6
Chapter 4: Genetic Algorithms
http://bit.ly/1sYEs1Q

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

You can download the pdf of this publication from here


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} }