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URN: urn:nbn:de:0030-drops-2543
URL: http://drops.dagstuhl.de/opus/volltexte/2005/254/

Mostaghim, Sanaz ; Teich, Jürgen

A New Approach on Many Objective Diversity Measurement

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Abstract

In multi-objective particle swarm optimization (MOPSO) methods, selecting the best {it local guide} (the global best particle) for each particle of the population from a set of Pareto-optimal solutions has a great impact on the convergence and diversity of solutions, especially when optimizing problems with high number of objectives. here, we introduce the Sigma method as a new method for finding best local guides for each particle of the population. The Sigma method is implemented and is compared with another method, which uses the strategy of an existing MOPSO method for finding the local guides. These methods are examined for different test functions and the results are compared with the results of a multi-objective evolutionary algorithm (MOEA).

BibTeX - Entry

@InProceedings{mostaghim_et_al:DSP:2005:254,
  author =	{Sanaz Mostaghim and J{\"u}rgen Teich},
  title =	{A New Approach on Many Objective Diversity Measurement},
  booktitle =	{Practical Approaches to Multi-Objective Optimization},
  year =	{2005},
  editor =	{J{\"u}rgen Branke and Kalyanmoy Deb and Kaisa Miettinen and Ralph E. Steuer},
  number =	{04461},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Internationales Begegnungs- und Forschungszentrum f{\"u}r Informatik (IBFI), Schloss Dagstuhl, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2005/254},
  annote =	{Keywords: Multi-objective Optimization, Particle Swarm Optimization}
}

Keywords: Multi-objective Optimization, Particle Swarm Optimization
Seminar: 04461 - Practical Approaches to Multi-Objective Optimization
Issue date: 2005
Date of publication: 10.08.2005


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