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Diversity metric assessment for multi-objective optimization

Radhi, H.E. and Barrans, Simon (2013) Diversity metric assessment for multi-objective optimization. In: Proceedings of Computing and Engineering Annual Researchers' Conference 2013 : CEARC'13. University of Huddersfield, Huddersfield, pp. 171-175. ISBN 9781862181212

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Abstract

In multi-objective optimization evolutionary algorithms (MOEA) diversity is an important issue and many researchers have investigated this notion. Due to the importance of multi-objective optimization in industry and engineering, it is essential to find a diverse set of Pareto optimal solutions which covers as much space as possible in the feasible region of the solution space. Theresearch (2012) presented in this paper aims to examine the performance and compare two metrics for diversity assessment of the non-dominated solution (i.e. Pareto set) in the solution space. These two metrics have been programmed in (MATLAB) software and implemented in number of simple bi-objective optimization cases to compare the analytical results with the visual distribution of points. The experimental results show that the circumscription diversity (CM) metric outperforms the Pair Wise (PW) metric

Item Type: Book Chapter
Uncontrolled Keywords: Multi-objective optimization, Diversity metrics.
Subjects: T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
Schools: School of Computing and Engineering
School of Computing and Engineering > Centre for Precision Technologies > Engineering Control and Machine Performance Research Group
School of Computing and Engineering > Computing and Engineering Annual Researchers' Conference (CEARC)
School of Computing and Engineering > Turbocharger Research Institute
Related URLs:
Depositing User: Sharon Beastall
Date Deposited: 18 Dec 2013 13:08
Last Modified: 02 Dec 2016 06:47
URI: http://eprints.hud.ac.uk/id/eprint/19383

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