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
I have published a few papers on Sports Scheduling.
http://bit.ly/gVaUqT

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Data Visualisation Competition

Publication(s)

The Cross-domain Heuristic Search Challenge - An International Research Competition
http://bit.ly/1a2VfMs
Scheduling English Football Fixtures: Consideration of Two Conflicting Objectives
http://bit.ly/er0RSP
Chapter 4: Genetic Algorithms
http://bit.ly/1sYEs1Q
Regulators as Ďagentsí: power and personality in risk regulation and a role for agent-based simulation
http://bit.ly/evaXWn

Graham Kendall: Details of Requested Publication


Citation

Han, L; Kendall, G and Cowling, P An Adaptive Length Chromosome Hyperheuristic Genetic Algorithm for a Trainer Scheduling Problem. In Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL2002), pages 267-271, Orchid Country Club, Singapore, November 18-22, 2002.


Abstract

Hyper-GA was introduced by the authors as a genetic algorithm based hyperheuristic which aims to evolve an ordering of low-level heuristics so as to find a good quality solution to a given problem. The adaptive length chromosome hyper-GA, letís call it ALChyper-GA, is an extension of the authors previous work, in which the chromosome was of fixed length. The aim of a variable length chromosome is two fold; 1) it allows dynamic removal and insertion of heuristics 2) it allows the GA to find a good chromosome length which could otherwise only be found by experimentation. We apply the ALChyper-GA to a geographically distributed training staff and courses scheduling problem, and report that good quality solution can be found. We also present results for four versions of the ALChyper-GA, applied to five test data sets.


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Bibtex

@INPROCEEDINGS{hkc2002, author = {L. Han and G. Kendall and P. Cowling},
title = {An Adaptive Length Chromosome Hyperheuristic Genetic Algorithm for a Trainer Scheduling Problem},
booktitle = {Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution And Learning (SEAL2002)},
year = {2002},
pages = {267--271},
address = {Orchid Country Club, Singapore, November 18-22},
abstract = {Hyper-GA was introduced by the authors as a genetic algorithm based hyperheuristic which aims to evolve an ordering of low-level heuristics so as to find a good quality solution to a given problem. The adaptive length chromosome hyper-GA, letís call it ALChyper-GA, is an extension of the authors previous work, in which the chromosome was of fixed length. The aim of a variable length chromosome is two fold; 1) it allows dynamic removal and insertion of heuristics 2) it allows the GA to find a good chromosome length which could otherwise only be found by experimentation. We apply the ALChyper-GA to a geographically distributed training staff and courses scheduling problem, and report that good quality solution can be found. We also present results for four versions of the ALChyper-GA, applied to five test data sets.},
keywords = {hyperheuristics, hyper-heuristics, genetic algorithms, GA},
timestamp = {2007.03.29},
webpdf = {http://www.graham-kendall.com/papers/hkc2002.pdf} }