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
http://bit.ly/1DXGeZD
Can ants play chess? Yes they can!
http://bit.ly/1yW3UhX

Latest Blog Post

How Isaac Newton could help you beat the casino at roulette

Random Blog Post

Improved Automatic Tweeting

Publication(s)

An Investigation of Automated Planograms Using a Simulated Annealing Based Hyper-heuristics
http://bit.ly/erH9W8
A Simulated Annealing Hyper-heuristic Methodology for Flexible Decision Support
http://bit.ly/1a34rQJ
An Investigation of an Adaptive Scheduling for Multi Headed Placement Machines Using a Greedy Search
http://bit.ly/g0DYmz
Learning with imperfections - a multi-agent neural-genetic trading system with differing levels of social learning
http://bit.ly/hBQypU

Graham Kendall: Details of Requested Publication


Citation

Angiz, M. L. Z; Nawawi, M. K. M; Khalid, R; Mustafa, A; Emrouznejad, A; John, R and Kendall, G Evaluating decision-making units under uncertainty using fuzzy multi-objective nonlinear programming. INFOR: Information Systems and Operational Research, 55 (1): 1-15, 2017.


Abstract

This paper proposes a new method to evaluate decision-making units (DMUs) under uncertainty using fuzzy data envelopment analysis (DEA). In the proposed multi-objective nonlinear programming methodology, both the objective functions and the constraints are considered fuzzy. This model is comprehensive in dealing with uncertainty, in the sense that coefficients of the decision variables in the objective functions and in the constraints, as well as the DMUs under assessment, are assumed to be fuzzy numbers with triangular membership functions. A comparison between the current fuzzy DEA models and the proposed method is illustrated by a numerical example.


pdf

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doi

The doi for this publication is 10.1080/03155986.2016.1240944 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.

2015 (0.095), 2014 (0.171), 2013 (0.410), 2012 (0.395), 2011 (0.295), 2010 (0.318), 2009 (0.738), 2008 (0.324), 2007 (0.275), 2006 (0.095), 2005 (0.195), 2004 (0.095), 2003 (0.125), 2002 (0.224), 2001 (0.319), 2000 (0.133)

URL

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Bibtex

@ARTICLE{ankmejk2017, author = {M. L. Z. Angiz and M. K. M. Nawawi and R. Khalid and A. Mustafa and A. Emrouznejad and R. John and G. Kendall},
title = {Evaluating decision-making units under uncertainty using fuzzy multi-objective nonlinear programming},
journal = {INFOR: Information Systems and Operational Research},
year = {2017},
volume = {55},
pages = {1--15},
number = {1},
abstract = {This paper proposes a new method to evaluate decision-making units (DMUs) under uncertainty using fuzzy data envelopment analysis (DEA). In the proposed multi-objective nonlinear programming methodology, both the objective functions and the constraints are considered fuzzy. This model is comprehensive in dealing with uncertainty, in the sense that coefficients of the decision variables in the objective functions and in the constraints, as well as the DMUs under assessment, are assumed to be fuzzy numbers with triangular membership functions. A comparison between the current fuzzy DEA models and the proposed method is illustrated by a numerical example.},
doi = {10.1080/03155986.2016.1240944},
eprint = { http://dx.doi.org/10.1080/03155986.2016.1240944 },
owner = {Graham},
timestamp = {2016.12.18} }