A New Approach on Many Objective Diversity Measurement
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Date
2005-08-10
Publication Type
Conference Paper
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yes
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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).
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Publication status
published
External links
Book title
Practical approaches to multi-objective optimization
Journal / series
Volume
4461
Pages / Article No.
1 - 15
Publisher
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Event
Dagstuhl Seminar 04461: Practical Approaches to Multi-Objective Optimization
Edition / version
Methods
Software
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Organisational unit
03643 - Halter, Werner (SNF-Professur) (ehem.)