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Memorias de investigación
Communications at congresses:
EDA-PSO: A Hybrid Paradigm Combining Estimation of Distribution Algorithms and Particle Swarm Optimization
Year:2010
Research Areas
  • Artificial intelligence
Information
Abstract
Estimation of Distribution Algorithms (EDAs) is an evolutionary computation optimization paradigm that relies the evolution of each generation on calculating a probabilistic graphical model able to reflect dependencies among variables out of the selected individuals of the population. This showed to be able to improve results with GAs for complex problems. This paper presents a new hybrid approach combining EDAs and particle swarm optimization, with the aim to take advantage of EDAs capability to learn from the dependencies between variables while profiting particle swarm¿s optimization ability to keep a sense of ¿direction¿ towards the most promising areas of the search space. Experimental results show the validity of this approach with widely known combinatorial optimization problems.
International
Si
Congress
7th International Conference ANTS 2010
960
Place
Bruselas
Reviewers
Si
ISBN/ISSN
3-642-15460-3
10.1007/978-3-642-15461-4_39
Start Date
08/09/2010
End Date
10/09/2010
From page
416
To page
423
Swarm Intelligence
Participants
  • Autor: Pedro Maria Larrañaga Mugica (UPM)
  • Participante: Endika Bengoetxea (Universidad del País Vasco)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: COMPUTATIONAL INTELLIGENCE GROUP
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