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

Help solve Santa's logistics problems
http://bit.ly/1DXreuW
I am the chair of the MISTA (Multidisciplinary International Conference on Scheduling: Theory and Applications)
http://bit.ly/hvZIaN

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

How academics can engage with policy

Publication(s)

A Hybrid Differential Evolution Algorithm - Game Theory for the Berth Allocation Problem
http://bit.ly/1OjS0k9
An efficient guided local search approach for service network design problem with asset balancing
http://bit.ly/fY7uch
A survey of surface mount device placement machine optimisation: Machine classification
http://bit.ly/hvQjOV
Optimisation for Surface Mount Placement Machines
http://bit.ly/fbcxGc

Graham Kendall: Details of Requested Publication


Citation

Burke, E.K; Q., Gu and Kendall, G A Hyper-Heuristic Approach to Strip Packing Problems. In Proceedings of Problem Parallel Solving from Nature (PPSN XI), Sep 2010, pages 465-474, Springer Berlin / Heidelberg, Lecture Notes in Computer Science 6238, 2011.


Abstract

In this paper we propose a genetic algorithm based hyper-heuristic for producing good quality solutions to strip packing problems. Instead of using just a single decoding heuristic, we employ a set of heuristics. This enables us to search a larger solution space without loss of efficiency. Empirical studies are presented on two-dimensional orthogonal strip packing problems which demonstrate that the algorithm operates well across a wide range of problem instances.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.1007/978-3-642-15844-5_47 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



URL

The URL for additional information is http://www.springer.com/computer/bioinformatics/book/978-3-642-15843-8

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{bgk2011, author = {E.K. Burke and Guo Q. and G. Kendall},
title = {A Hyper-Heuristic Approach to Strip Packing Problems},
booktitle = {Proceedings of Problem Parallel Solving from Nature (PPSN XI), Sep 2010},
year = {2011},
editor = {R. Schaefer and C. Cotta and J Kolodziej and G.Rudolph},
volume = {6238},
series = {Lecture Notes in Computer Science},
pages = {465-474},
month = {11-15 September 2010},
publisher = {Springer Berlin / Heidelberg},
abstract = {In this paper we propose a genetic algorithm based hyper-heuristic for producing good quality solutions to strip packing problems. Instead of using just a single decoding heuristic, we employ a set of heuristics. This enables us to search a larger solution space without loss of efficiency. Empirical studies are presented on two-dimensional orthogonal strip packing problems which demonstrate that the algorithm operates well across a wide range of problem instances.},
doi = {10.1007/978-3-642-15844-5_47},
keywords = {hyper-heuristics, cutting, packing, hyperheuristics},
owner = {gxk},
timestamp = {2010.12.09},
url = {http://www.springer.com/computer/bioinformatics/book/978-3-642-15843-8},
webpdf = {http://www.graham-kendall.com/papers/bgk2011.pdf} }