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 am a member of the Automated Scheduling, Optimisation and Planning Research Group
http://bit.ly/eIQ5XC
I blog occasionally, feel free to take a look.
http://bit.ly/hq6rMK

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Summer Conferences

Publication(s)

A Multi-objective Hyper-heuristic based on Choice Function
http://bit.ly/1f8GQgU
A New Dynamic Point Specification Approach to Optimise Surface Mount Placement Machine in Printed Circuit Board Assembly
http://bit.ly/hWCyZA
A New Approach to Packing Non-Convex Polygons Using the No Fit Polygon and Meta-Heuristic and Evolutionary Algorithms
http://bit.ly/eMYCKs
Applying Evolutionary Algorithms and the No Fit Polygon to the Nesting Problem
http://bit.ly/fT4zDt

Graham Kendall: Details of Requested Publication


Citation

Bai, R; Burke, E. K and Kendall, G Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation. Journal of the Operational Research Society, 59 (10): 1387-1397, 2008.


Abstract

The allocation of fresh produce to shelf space represents a new decision support research area which is motivated by the desire of many retailers to improve their service due to the increasing demand for fresh food. However, automated decision making for fresh produce allocation is challenging because of the very short lifetime of fresh products. This paper considers a recently proposed practical model for the problem which is motivated by our collaboration with Tesco. Moreover, the paper investigates heuristic and meta-heuristic approaches as alternatives for the generalized reduced gradient algorithm, which becomes inefficient when the problem size becomes larger. A simpler single-item inventory problem is firstly studied and solved by a polynomial time bounded procedure. Several dynamic greedy heuristics are then developed for the multi-item problem based on the procedure for the single-item inventory problem. Experimental results show that these greedy heuristics are much more efficient and provide competitive results when compared to those of a multi-start generalized reduced gradient algorithm. In order to further improve the solution, we investigated simulated annealing, a greedy randomized adaptive search procedure and three types of hyper-heuristics. Their performance is tested and compared on a set of problem instances which are made publicly available for the research community.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.1057/palgrave.jors.2602463 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

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{bbk2008, author = {R. Bai and E. K. Burke and G. Kendall},
title = {Heuristic, meta-heuristic and hyper-heuristic approaches for fresh produce inventory control and shelf space allocation},
journal = {Journal of the Operational Research Society},
year = {2008},
volume = {59},
pages = {1387--1397},
number = {10},
abstract = {The allocation of fresh produce to shelf space represents a new decision support research area which is motivated by the desire of many retailers to improve their service due to the increasing demand for fresh food. However, automated decision making for fresh produce allocation is challenging because of the very short lifetime of fresh products. This paper considers a recently proposed practical model for the problem which is motivated by our collaboration with Tesco. Moreover, the paper investigates heuristic and meta-heuristic approaches as alternatives for the generalized reduced gradient algorithm, which becomes inefficient when the problem size becomes larger. A simpler single-item inventory problem is firstly studied and solved by a polynomial time bounded procedure. Several dynamic greedy heuristics are then developed for the multi-item problem based on the procedure for the single-item inventory problem. Experimental results show that these greedy heuristics are much more efficient and provide competitive results when compared to those of a multi-start generalized reduced gradient algorithm. In order to further improve the solution, we investigated simulated annealing, a greedy randomized adaptive search procedure and three types of hyper-heuristics. Their performance is tested and compared on a set of problem instances which are made publicly available for the research community.},
doi = {10.1057/palgrave.jors.2602463},
issn = {0160-5682},
keywords = {meta-heuristics, hyper-heuristics, shelf space allocation, inventory, fresh produce, hyperheuristics, metaheuristics},
timestamp = {2008.02.28},
webpdf = {http://www.graham-kendall.com/papers/bbk2008.pdf} }