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 to teach Deep Blue to play poker and deliver groceries
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What do we spend so much in supermarkets?
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Publication(s)

A multi-agent based simulated stock market - testing on different types of stocks
http://bit.ly/haEt18
Studying the Effect that a Linear Transformation has on the Time-Series Prediction Ability of an Evolutionary Neural Network
http://bit.ly/eyLaq2
Choice Function based Hyper-heuristics for Multi-objective Optimization
http://bit.ly/1rquSdW
Heuristic Space Diversity Management in a Meta-Hyper-Heuristic Framework
http://bit.ly/1uuQW45

Graham Kendall: Details of Requested Publication


Citation

Kendall, G and Mohamad, Solving the Fixed Channel Assignment Problem in Cellular Communications Using An Adaptive Local Search. In Proceedings of the 5th international conference on the Practice and Theory of Automated Timetabling (PATAT 2004), pages 219-231, Pittsburgh, USA, 2004.


Abstract

The Channel Assignment Problem can be defined as assigning a minimum number of radio frequencies to a set of transceiver/receiver units without violating given constraints, in particular the frequency separation that must exist between two given channels to avoid interference. Being an NP-complete problem, finding good quality solutions increases in difficulty as the number of transceiver/receiver units increase. Previous approaches for solving the channel assignment problems have used graph colouring, heuristic ap-proaches, local search, meta-heuristics and genetic algorithms. In this paper, we present a greedy local search, combined with a monte carlo algorithm as an ac-ceptance criteria. Our results are able to match lower bound conditions and beat existing approaches. Computational results are given.


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Bibtex

@INPROCEEDINGS{km2004c, author = {G. Kendall and M Mohamad},
title = {Solving the Fixed Channel Assignment Problem in Cellular Communications Using An Adaptive Local Search},
booktitle = {Proceedings of the 5th international conference on the Practice and Theory of Automated Timetabling (PATAT 2004)},
year = {2004},
pages = {219--231},
address = {Pittsburgh, USA},
month = {18-20 August},
abstract = {The Channel Assignment Problem can be defined as assigning a minimum number of radio frequencies to a set of transceiver/receiver units without violating given constraints, in particular the frequency separation that must exist between two given channels to avoid interference. Being an NP-complete problem, finding good quality solutions increases in difficulty as the number of transceiver/receiver units increase. Previous approaches for solving the channel assignment problems have used graph colouring, heuristic ap-proaches, local search, meta-heuristics and genetic algorithms. In this paper, we present a greedy local search, combined with a monte carlo algorithm as an ac-ceptance criteria. Our results are able to match lower bound conditions and beat existing approaches. Computational results are given.},
keywords = {Channel Assignment, local search, adaptive, frequency assignment},
timestamp = {2007.03.29},
webpdf = {http://www.graham-kendall.com/papers/km2004c.pdf} }