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 have wriiten a number of articles for TheConversation
http://bit.ly/1yWlOkE
A Conversation article celebrating Pi
http://bit.ly/1DXuXbV

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

Examination Timetabling: Carter Dataset

Publication(s)

A local search approach to a circle cutting problem arising in the motor cycle industry
http://bit.ly/dJxzGW
Providing a memory mechanism to enhance the evolutionary design of heuristics
http://bit.ly/fd4uYt
Co-Evolving Neural networks with Evolutionary Strategies: A New Application to Divisia Money
http://bit.ly/eBV6pc
Evolutionary Strategies vs. Neural Networks: An Inflation Forecasting Experiment
http://bit.ly/h6J8Xv

Graham Kendall: Details of Requested Publication


Citation

Kendall, G and Westphal, S Sports Scheduling: Minimizing Travel for English Football Supporters. In Autoomated Scheduling and Planning: Studies in Computational Intelligence, pages 61-90, Springer Berlin Heidelberg, 2013.

This book chapter is part of the book Automated Scheduling and Planning


Abstract

The football authorities in England are responsible for generating the fixtures for the entire football season but the fixtures that are played over the Christmas period are given special consideration as they represent the minimum distances that are traveled by supporters when compared with fixtures played at other times of the year. The distances are minimized at this time of the year to save supporters having to travel long distances during the holiday period, which often coincides with periods of bad weather. In addition, the public transport system has limited services on some of the days in question. At this time of the year every team is required to play, which is not always the case for the rest of the season.When every team is required to play, we refer to this as a complete fixture. Additionally, each team has to to play a home game and an away game. Therefore, over the Christmas period we are required to produce two complete fixtures, where each team has to have a Home/Away pattern of HA or AH. In some seasons four complete fixtures are generated where each team is required to have a Home/Away pattern of HAHA (or AHAH).Whether two or four fixtures are generated there are various other constraints that have to be respected. For example, the same teams cannot play each other and we have to avoid (as far as possible) having some teams play at home on the same day. This chapter has three main elements. i) An analysis of seven seasons to classify them as two or four fixture seasons. ii) The presentation of a single mathematical model that is able to generate both two and four fixture schedules which adheres to all the required constraints. Additionally, the model is parameterized so that we can conduct a series of experiments. iii) Demonstrating that the model is able to produce solutions which are superior to the solutions that were used in practise (the published fixtures) and which are also superior to our previous work. The solutions we generate are near optimal for the two fixture case. The four fixture case is more challenging and the solutions are about 16% of the lower bound. However, they are still a significant improvement on the fixtures that were actually used. We also show, through three experimental setups, that the problem owner might actually not want to accept the best solution with respect to the overall minimized distance but might want to take a slightly worse solution but which offers a guarantee as to the maximum distance that has to be traveled by the supporters within each division.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.1007/978-3-642-39304-4_3 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

The URL for additional information is http://rd.springer.com/book/10.1007/978-3-642-39304-4/

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

@INBOOK{kw2013, chapter = {Autoomated Scheduling and Planning: Studies in Computational Intelligence},
pages = {61--90},
title = {Sports Scheduling: Minimizing Travel for English Football Supporters},
publisher = {Springer Berlin Heidelberg},
year = {2013},
editor = {A.S. Uyar and E. {"O}zcan and N. Urquhart},
author = {G. Kendall and S. Westphal},
volume = {505},
note = {This book chapter is part of the book Automated Scheduling and Planning},
abstract = {The football authorities in England are responsible for generating the fixtures for the entire football season but the fixtures that are played over the Christmas period are given special consideration as they represent the minimum distances that are traveled by supporters when compared with fixtures played at other times of the year. The distances are minimized at this time of the year to save supporters having to travel long distances during the holiday period, which often coincides with periods of bad weather. In addition, the public transport system has limited services on some of the days in question. At this time of the year every team is required to play, which is not always the case for the rest of the season.When every team is required to play, we refer to this as a complete fixture. Additionally, each team has to to play a home game and an away game. Therefore, over the Christmas period we are required to produce two complete fixtures, where each team has to have a Home/Away pattern of HA or AH. In some seasons four complete fixtures are generated where each team is required to have a Home/Away pattern of HAHA (or AHAH).Whether two or four fixtures are generated there are various other constraints that have to be respected. For example, the same teams cannot play each other and we have to avoid (as far as possible) having some teams play at home on the same day. This chapter has three main elements. i) An analysis of seven seasons to classify them as two or four fixture seasons. ii) The presentation of a single mathematical model that is able to generate both two and four fixture schedules which adheres to all the required constraints. Additionally, the model is parameterized so that we can conduct a series of experiments. iii) Demonstrating that the model is able to produce solutions which are superior to the solutions that were used in practise (the published fixtures) and which are also superior to our previous work. The solutions we generate are near optimal for the two fixture case. The four fixture case is more challenging and the solutions are about 16% of the lower bound. However, they are still a significant improvement on the fixtures that were actually used. We also show, through three experimental setups, that the problem owner might actually not want to accept the best solution with respect to the overall minimized distance but might want to take a slightly worse solution but which offers a guarantee as to the maximum distance that has to be traveled by the supporters within each division.},
doi = {10.1007/978-3-642-39304-4_3},
keywords = {Sports, Scheduling, Football},
owner = {jvb},
timestamp = {2008.09.30},
url = {http://rd.springer.com/book/10.1007/978-3-642-39304-4/},
webpdf = {http://www.graham-kendall.com/papers/kw2013.pdf} }