Graham Kendall
Various Images

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 am the chair of the MISTA (Multidisciplinary International Conference on Scheduling: Theory and Applications)
http://bit.ly/hvZIaN
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

Knight’s Tour

Publication(s)

The Effects of Extra-Somatic Weapons on the Evolution of Human Cooperation towards Non-Kin
http://bit.ly/1oXDe7O
Collective Behavior and Kin Selection in Evolutionary IPD
http://bit.ly/if34nF
Alternative hyper-heuristic strategies for multi-method global optimization
http://bit.ly/g1xcMp
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

Petrovic, S; Fayad, C; Petrovic, D; Burke, E and Kendall, G Fuzzy job shop scheduling with lot-sizing. Annals of Operations Research, 159 (1): 275-292, 2008.


Abstract

This paper deals with a problem of determining lot-sizes of jobs in a real-world job shop-scheduling in the presence of uncertainty. The main issue discussed in this paper is lot-sizing of jobs. A fuzzy rule-based system is developed which determines the size of lots using the following premise variables: size of the job, the static slack of the job, workload on the shop floor, and the priority of the job. Both premise and conclusion variables are modelled as linguistic variables represented by using fuzzy sets (apart from the priority of the job which is a crisp value). The determined lotsí sizes are input to a fuzzy multi-objective genetic algorithm for job shop scheduling. Imprecise jobsí processing times and due dates are modelled by using fuzzy sets. The objectives that are used to measure the quality of the generated schedules are average weighted tardiness of jobs, the number of tardy jobs, the total setup time, the total idle time of machines and the total flow time of jobs. The developed algorithm is analysed on real-world data obtained from a printing company.


pdf

You can download the pdf of this publication from here


doi

The doi for this publication is 10.1007/s10479-007-0287-9 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


Journal Rankings


ISI Web of Knowledge Journal Citation Reports

The Web of Knowledge Journal Citation Reports (often known as ISI Impact Factors) help measure how often an article is cited. You can get an introduction to Journal Citation Reports here. Below I have provided the ISI impact factor for the jourrnal in which this article was published. For complete information I have shown the ISI ranking over a number of years, with the latest ranking highlighted.

2014 (1.217), 2013 (1.103), 2012 (1.029), 2011 (0.840), 2010 (0.840), 2010 (0.675), 2009 (0.961), 2008 (0.619), 2007 (0.544), 2006 (0.589), 2005 (0.525), 2004 (0.411), 2003 (0.331), 2002 (0.258), 2001 (0.255), 2000 (0.364)

URL

This pubication does not have a URL associated with it.

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

@ARTICLE{pfpbk2008, author = {S. Petrovic and C. Fayad and D. Petrovic and E. Burke and G. Kendall},
title = {Fuzzy job shop scheduling with lot-sizing},
journal = {Annals of Operations Research},
year = {2008},
volume = {159},
pages = {275--292},
number = {1},
abstract = {This paper deals with a problem of determining lot-sizes of jobs in a real-world job shop-scheduling in the presence of uncertainty. The main issue discussed in this paper is lot-sizing of jobs. A fuzzy rule-based system is developed which determines the size of lots using the following premise variables: size of the job, the static slack of the job, workload on the shop floor, and the priority of the job. Both premise and conclusion variables are modelled as linguistic variables represented by using fuzzy sets (apart from the priority of the job which is a crisp value). The determined lotsí sizes are input to a fuzzy multi-objective genetic algorithm for job shop scheduling. Imprecise jobsí processing times and due dates are modelled by using fuzzy sets. The objectives that are used to measure the quality of the generated schedules are average weighted tardiness of jobs, the number of tardy jobs, the total setup time, the total idle time of machines and the total flow time of jobs. The developed algorithm is analysed on real-world data obtained from a printing company.},
doi = {10.1007/s10479-007-0287-9},
issn = {0254-5330},
keywords = {Job shop scheduling, Fuzzy rule-based system, Lot-sizing , Batching, Fuzzy, multi-objective, genetic algorithm, Real-world application, Dispatching rules},
owner = {jqf},
timestamp = {2007.11.08},
webpdf = {http://www.graham-kendall.com/papers/pfpbk2008.pdf} }