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

A Conversation article celebrating Pi
http://bit.ly/1DXuXbV
What do we spend so much in supermarkets?
http://bit.ly/1yW6If7

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Bin Packing Made Easier?

Publication(s)

An Iterated Local Search with Multiple Perturbation Operators and Time Varying Perturbation Steength for the Aircraft Landing Problem
http://bit.ly/1KJ1818
Channel Assignment Optimisation Using a Hyper-Heuristic
http://bit.ly/eIazTf
Enumerating knight's tours using an ant colony algorithm
http://bit.ly/fMCY7C
A Variable Neighborhood Descent Search Algorithm for Delay-Constrained Least-Cost Multicast Routing
http://bit.ly/h1puUB

Graham Kendall: Details of Requested Publication


Citation

Han, L and Kendall, G An investigation of a tabu assisted hyper-heuristic genetic algorithm. In Proceedings of the The IEEE 2003 Congress on Evolutionary Computation (CEC2003), pages 2230-2237, Canberra, Australia, 2003.


Abstract

This paper investigates a tabu assisted genetic algorithm based hyper-heuristic (hyper-TGA) for personnel scheduling problems. We recently introduced a hyper-heuristic genetic algorithm (hyper-GA) with an adaptive length chromosome which aims to evolve an ordering of low-level heuristics in order to find good quality solutions to given problems. The addition of a tabu method, the focus of this paper, extends that work. The aim of adding a tabu list to the hyper-GA is to indicate the efficiency of each gene within the chromosome. We apply the algorithm to a geographically distributed training staff and course scheduling problem and compare the computational results with our previous hyper-GA.


pdf

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doi

The doi for this publication is 10.1109/CEC.2003.1299949 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

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Bibtex

@INPROCEEDINGS{hk2003, author = {L. Han and G. Kendall},
title = {An investigation of a tabu assisted hyper-heuristic genetic algorithm},
booktitle = {Proceedings of the The IEEE 2003 Congress on Evolutionary Computation (CEC2003)},
year = {2003},
volume = {3},
pages = {2230--2237},
address = {Canberra, Australia},
month = {Dec 8 - 12},
abstract = {This paper investigates a tabu assisted genetic algorithm based hyper-heuristic (hyper-TGA) for personnel scheduling problems. We recently introduced a hyper-heuristic genetic algorithm (hyper-GA) with an adaptive length chromosome which aims to evolve an ordering of low-level heuristics in order to find good quality solutions to given problems. The addition of a tabu method, the focus of this paper, extends that work. The aim of adding a tabu list to the hyper-GA is to indicate the efficiency of each gene within the chromosome. We apply the algorithm to a geographically distributed training staff and course scheduling problem and compare the computational results with our previous hyper-GA.},
comment = {IEEE Catalog Number: 03TH8674, ISBN: 0-7803-7804-0},
doi = {10.1109/CEC.2003.1299949},
keywords = {hyper-heuristic, hyperheyristic, genetic algorithm, tabu search, personnel scheduling, rostering, timetabling},
timestamp = {2007.03.29},
webpdf = {http://www.graham-kendall.com/papers/hk2003.pdf} }