A New Approach on Many Objective Diversity Measurement

Mostaghim, Sanaz; Teich, Jürgen

doi:10.4230/DagSemProc.04461.4

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A New Approach on Many Objective Diversity Measurement

Authors Sanaz Mostaghim, Jürgen Teich

Part of: Volume: Dagstuhl Seminar Proceedings, Volume 4461
Part of: Series: Dagstuhl Seminar Proceedings (DagSemProc)
License: Creative Commons Attribution 4.0 International license
Publication Date: 2005-08-10

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Document Identifiers

DOI: 10.4230/DagSemProc.04461.4
URN: urn:nbn:de:0030-drops-2543

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Keywords

Multi-objective Optimization
Particle Swarm Optimization

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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).

Cite As Get BibTex

Sanaz Mostaghim and Jürgen Teich. A New Approach on Many Objective Diversity Measurement. In Practical Approaches to Multi-Objective Optimization. Dagstuhl Seminar Proceedings, Volume 4461, pp. 1-15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005) https://doi.org/10.4230/DagSemProc.04461.4

Author Details

Sanaz Mostaghim

Jürgen Teich

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