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
Can ants play chess? Yes they can!
http://bit.ly/1yW3UhX

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

2015 General Election Prediction: Wisdom of the Crowds

Publication(s)

A Variable Neighborhood Descent Search Algorithm for Delay-Constrained Least-Cost Multicast Routing
http://bit.ly/h1puUB
The effect of memory size on the evolutionary stability of strategies in iterated prisoner's dilemma
http://bit.ly/1HXMzXa
Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation
http://bit.ly/dH42Fp
A path-oriented encoding evolutionary algorithm for network coding resource minimization
http://bit.ly/1t0cd2K

Graham Kendall: Details of Requested Publication


Citation

Bai, R; Kendall, G; Qu, R and Atkin, J Tabu assisted guided local search approaches for freight service network design. Information Sciences, 189: 266-281, 2012.


Abstract

The service network design problem (SNDP) is a core problem in freight transportation. It involves the determination of the most cost-effective transportation network and the characteristics of the corresponding services, subject to various constraints. The scale of the problem in real-world applications is usually very large, especially when the network contains both the geographical information and the temporal constraints which are necessary for modelling multiple service-classes and dynamic events. The development of time-efficient algorithms for this problem is, therefore, crucial for successful real-world applications. Earlier research indicated that guided local search (GLS) was a promising solution method for this problem. One of the advantages of GLS is that it makes use of both the information collected during the search as well as any special structures which are present in solutions. Building upon earlier research, this paper carries out in-depth investigations into several mechanisms that could potentially speed up the GLS algorithm for the SNDP. Specifically, the mechanisms that we have looked at in this paper include a tabu list (as used by tabu search), short-term memory, and an aspiration criterion. An efficient hybrid algorithm for the SNDP is then proposed, based upon the results of these experiments. The algorithm combines a tabu list within a multi-start GLS approach, with an efficient feasibility-repairing heuristic. Experimental tests on a set of 24 well-known service network design benchmark instances have shown that the proposed algorithm is superior to a previously proposed tabu search method, reducing the computation time by over a third. In addition, we also show that far better results can be obtained when a faster linear program solver is adopted for the sub-problem solution. The contribution of this paper is an efficient algorithm, along with detailed analyses of effective mechanisms which can help to increase the speed of the GLS algorithm for the SNDP.


pdf

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doi

The doi for this publication is 10.1016/j.ins.2011.11.028 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 (4.038), 2013 (3.893), 2012 (3.643), 2011 (2.833), 2010 (2.836), 2009 (3.291), 2008 (3.095), 2007 (2.147), 2006 (1.003), 2005 (0.723), 2004 (0.540), 2003 (0.447), 2002 (0.361), 2001 (0.264), 2000 (0.322)

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{bkqa2012, author = {R. Bai and G. Kendall and R. Qu and J. Atkin},
title = {Tabu assisted guided local search approaches for freight service network design},
journal = {Information Sciences},
year = {2012},
volume = {189},
pages = {266--281},
abstract = {The service network design problem (SNDP) is a core problem in freight transportation. It involves the determination of the most cost-effective transportation network and the characteristics of the corresponding services, subject to various constraints. The scale of the problem in real-world applications is usually very large, especially when the network contains both the geographical information and the temporal constraints which are necessary for modelling multiple service-classes and dynamic events. The development of time-efficient algorithms for this problem is, therefore, crucial for successful real-world applications. Earlier research indicated that guided local search (GLS) was a promising solution method for this problem. One of the advantages of GLS is that it makes use of both the information collected during the search as well as any special structures which are present in solutions. Building upon earlier research, this paper carries out in-depth investigations into several mechanisms that could potentially speed up the GLS algorithm for the SNDP. Specifically, the mechanisms that we have looked at in this paper include a tabu list (as used by tabu search), short-term memory, and an aspiration criterion. An efficient hybrid algorithm for the SNDP is then proposed, based upon the results of these experiments. The algorithm combines a tabu list within a multi-start GLS approach, with an efficient feasibility-repairing heuristic. Experimental tests on a set of 24 well-known service network design benchmark instances have shown that the proposed algorithm is superior to a previously proposed tabu search method, reducing the computation time by over a third. In addition, we also show that far better results can be obtained when a faster linear program solver is adopted for the sub-problem solution. The contribution of this paper is an efficient algorithm, along with detailed analyses of effective mechanisms which can help to increase the speed of the GLS algorithm for the SNDP.},
doi = {10.1016/j.ins.2011.11.028},
issn = {0020-0255},
keywords = {Tabu Search, TS, Logistics, Freight, Guided Local Search, Linear Programming},
owner = {gxk},
timestamp = {2011.12.04},
webpdf = {http://www.graham-kendall.com/papers/bkqa2012.pdf} }