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

What do we spend so much in supermarkets?
http://bit.ly/1yW6If7
The hunt for MH370
http://bit.ly/1DXRLbu

Latest Blog Post

Snooker: Celebrating 40 years at the Crucible

Random Blog Post

MISTA Conference: Venue for 2011 announced

Publication(s)

Solving the Fixed Channel Assignment Problem in Cellular Communications Using An Adaptive Local Search
http://bit.ly/icGZM5
Evolving Reusable 3D Packing Heuristics with Genetic Programming.
http://bit.ly/e75y7F
Hyper-heuristics
http://bit.ly/1a2WNWE
Hybrid Heuristic for Multi-carrier Transportation Plans
http://bit.ly/1dGGwqO

Graham Kendall: Details of Requested Publication


Citation

Sabar, N. R and Kendall, G Using Harmony Search with Multiple Pitch Adjustment Operators for the Portfolio Selection Problem. In Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC 2014), pages 499-503, 2014.


Abstract

Portfolio selection is an important problem in the financial markets that seeks to distribute an amount of money over a set of assets where the goal is to simultaneously maximize the return and minimize the risk. In this work, we propose a harmony search algorithm (HSA) for this problem. HSA is a population based algorithm that mimics the musician improvisation process in solving optimization problems. At each iteration, HSA generates a new solution using a memory procedure which considers all existing solutions and then perturbs them using a pitch adjustment operator. To deal with different instances, and also changes in the problem landscape, we propose an improved HSA that utilizes multiple pitch adjustment operators. The rationale behind this is that different operators are appropriate for different stages of the search and using multiple operators can enhance the effectiveness of HSA. To evaluate and validate the effectiveness of the proposed HSA, computational experiments are carried out using portfolio selection benchmark instances from the scientific literature. The results demonstrate that the proposed HSA is capable of producing high quality solutions for most of the tested instances when compared with state of the art methods.


pdf

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doi

The doi for this publication is 10.1109/CEC.2014.6900384 You can link directly to the original paper, via the doi, from here

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Bibtex

@INPROCEEDINGS{sk2014b, author = {N. R. Sabar and G. Kendall},
title = {Using Harmony Search with Multiple Pitch Adjustment Operators for the Portfolio Selection Problem},
booktitle = {Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC 2014)},
year = {2014},
pages = {499--503},
abstract = {Portfolio selection is an important problem in the financial markets that seeks to distribute an amount of money over a set of assets where the goal is to simultaneously maximize the return and minimize the risk. In this work, we propose a harmony search algorithm (HSA) for this problem. HSA is a population based algorithm that mimics the musician improvisation process in solving optimization problems. At each iteration, HSA generates a new solution using a memory procedure which considers all existing solutions and then perturbs them using a pitch adjustment operator. To deal with different instances, and also changes in the problem landscape, we propose an improved HSA that utilizes multiple pitch adjustment operators. The rationale behind this is that different operators are appropriate for different stages of the search and using multiple operators can enhance the effectiveness of HSA. To evaluate and validate the effectiveness of the proposed HSA, computational experiments are carried out using portfolio selection benchmark instances from the scientific literature. The results demonstrate that the proposed HSA is capable of producing high quality solutions for most of the tested instances when compared with state of the art methods.},
doi = {10.1109/CEC.2014.6900384},
owner = {Graham},
timestamp = {2014.08.08},
webpdf = {http://www.graham-kendall.com/papers/sk2014b.pdf} }