The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Este artigo apresenta um novo otimizador de enxame de partículas caracterizado pela topologia de árvore crescente. Se uma partícula estiver estagnada, uma nova partícula nasce e fica localizada longe da armadilha. Dependendo da propriedade dos problemas objetivos, as partículas nascem sucessivamente e o enxame crescente constitui uma topologia em árvore. Realizando experimentos numéricos para benchmarks típicos, a eficiência do algoritmo é avaliada em diversas medidas importantes, como taxa de sucesso, número de iterações e número de partículas. Em comparação com outros PSOs básicos, podemos sugerir que o algoritmo proposto possui desempenho eficiente em otimização com computação de baixo custo.
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Eiji MIYAGAWA, Toshimichi SAITO, "Particle Swarm Optimizers with Growing Tree Topology" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 9, pp. 2275-2282, September 2009, doi: 10.1587/transfun.E92.A.2275.
Abstract: This paper presents a new particle swarm optimizer characterized by growing tree topology. If a particle is stagnated then a new particle is born and is located away from the trap. Depending on the property of objective problems, particles are born successively and the growing swarm constitutes a tree-topology. Performing numerical experiments for typical benchmarks, the algorithm efficiency is evaluated in several key measures such as success rate, the number of iterations and the number of particles. As compared with other basic PSOs, we can suggest that the proposed algorithm has efficient performance in optimization with low-cost computation.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.2275/_p
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@ARTICLE{e92-a_9_2275,
author={Eiji MIYAGAWA, Toshimichi SAITO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Particle Swarm Optimizers with Growing Tree Topology},
year={2009},
volume={E92-A},
number={9},
pages={2275-2282},
abstract={This paper presents a new particle swarm optimizer characterized by growing tree topology. If a particle is stagnated then a new particle is born and is located away from the trap. Depending on the property of objective problems, particles are born successively and the growing swarm constitutes a tree-topology. Performing numerical experiments for typical benchmarks, the algorithm efficiency is evaluated in several key measures such as success rate, the number of iterations and the number of particles. As compared with other basic PSOs, we can suggest that the proposed algorithm has efficient performance in optimization with low-cost computation.},
keywords={},
doi={10.1587/transfun.E92.A.2275},
ISSN={1745-1337},
month={September},}
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TY - JOUR
TI - Particle Swarm Optimizers with Growing Tree Topology
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 2275
EP - 2282
AU - Eiji MIYAGAWA
AU - Toshimichi SAITO
PY - 2009
DO - 10.1587/transfun.E92.A.2275
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 2009
AB - This paper presents a new particle swarm optimizer characterized by growing tree topology. If a particle is stagnated then a new particle is born and is located away from the trap. Depending on the property of objective problems, particles are born successively and the growing swarm constitutes a tree-topology. Performing numerical experiments for typical benchmarks, the algorithm efficiency is evaluated in several key measures such as success rate, the number of iterations and the number of particles. As compared with other basic PSOs, we can suggest that the proposed algorithm has efficient performance in optimization with low-cost computation.
ER -