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

Does AI have a place in the board room?
http://bit.ly/1DXreuW
I have published a few papers on Sports Scheduling.
http://bit.ly/gVaUqT

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

Some of the Challenges in Parsing Bibtex Authors

Publication(s)

A Multi-objective Hyper-heuristic based on Choice Function
http://bit.ly/1f8GQgU
Evolving human-competitive reusable 2D strip packing heuristics
http://bit.ly/f4msct
An investigation of a hyperheuristic genetic algorithm applied to a trainer scheduling problem
http://bit.ly/egxt0d
A Hyper-Heuristic Approach to Strip Packing Problems
http://bit.ly/fkNqJz

Graham Kendall: Details of Requested Publication


Citation

Xing, H; Qu, R; Kendall, G and Bai, R A path-oriented encoding evolutionary algorithm for network coding resource minimization. Journal of the Operational Research Society, 65 (8): 1261-1277, 2014.

ISSN: 0160-5682


Abstract

Network coding is an emerging telecommunication technique, where any intermediate node is allowed to recombine incoming data if necessary. This technique helps to increase the throughput, however, very likely at the cost of huge amount of computational overhead, due to the packet recombination performed (ie coding operations). Hence, it is of practical importance to reduce coding operations while retaining the benefits that network coding brings to us. In this paper, we propose a novel evolutionary algorithm (EA) to minimize the amount of coding operations involved. Different from the state-of-the-art EAs which all use binary encodings for the problem, our EA is based on path-oriented encoding. In this new encoding scheme, each chromosome is represented by a union of paths originating from the source and terminating at one of the receivers. Employing path-oriented encoding leads to a search space where all solutions are feasible, which fundamentally facilitates more efficient search of EAs. Based on the new encoding, we develop three basic operators, that is, initialization, crossover and mutation. In addition, we design a local search operator to improve the solution quality and hence the performance of our EA. The simulation results demonstrate that our EA significantly outperforms the state-of-the-art algorithms in terms of global exploration and computational time.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.1057/jors.2013.79 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 (0.953), 2013 (0.911), 2012 (0.989), 2011 (0.971), 2010 (1.102), 2009 (1.009), 2008 (0.839), 2007 (0.784), 2006 (0.597), 2005 (0.603), 2004 (0.515), 2003 (0.416), 2002 (0.493), 2001 (0.438), 2000 (0.648)

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{xqkb2014, author = {H. Xing and R. Qu and G. Kendall and R. Bai},
title = {A path-oriented encoding evolutionary algorithm for network coding resource minimization},
journal = {Journal of the Operational Research Society},
year = {2014},
volume = {65},
pages = {1261--1277},
number = {8},
note = {ISSN: 0160-5682},
abstract = {Network coding is an emerging telecommunication technique, where any intermediate node is allowed to recombine incoming data if necessary. This technique helps to increase the throughput, however, very likely at the cost of huge amount of computational overhead, due to the packet recombination performed (ie coding operations). Hence, it is of practical importance to reduce coding operations while retaining the benefits that network coding brings to us. In this paper, we propose a novel evolutionary algorithm (EA) to minimize the amount of coding operations involved. Different from the state-of-the-art EAs which all use binary encodings for the problem, our EA is based on path-oriented encoding. In this new encoding scheme, each chromosome is represented by a union of paths originating from the source and terminating at one of the receivers. Employing path-oriented encoding leads to a search space where all solutions are feasible, which fundamentally facilitates more efficient search of EAs. Based on the new encoding, we develop three basic operators, that is, initialization, crossover and mutation. In addition, we design a local search operator to improve the solution quality and hence the performance of our EA. The simulation results demonstrate that our EA significantly outperforms the state-of-the-art algorithms in terms of global exploration and computational time.},
doi = {10.1057/jors.2013.79},
issn = {0160-5682},
owner = {Graham},
timestamp = {2013.08.03},
webpdf = {http://www.graham-kendall.com/papers/xqkb2014.pdf} }