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

How are university examinations scheduled?
http://bit.ly/1z0pG4s
Help solve Santa's logistics problems
http://bit.ly/1DXreuW

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

3D Bin Packing, help Santa and share $10,000

Publication(s)

A Tabu-Search Hyperheuristic for Timetabling and Rostering
http://bit.ly/i7823Y
Making Airline Schedules More Robust
http://bit.ly/hbGm4B
Measuring the Robustness of Airline Fleet Schedules
http://bit.ly/1mlqXcv
A hyper-heuristic approach to sequencing by hybridization of DNA sequences
http://bit.ly/1mlNjL6

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} }