IEICE TRANSACTIONS on Fundamentals
Improvement of the Solving Performance by the Networking of Particle Swarm Optimization
Summary :
This paper presents a particle swarm optimization network (PSON) to improve the search capability of PSO. In PSON, multi-PSOs are connected for the purpose of communication. A variety of network topology can be realized by varying the number of connected PSOs of each PSO. The solving performance and convergence speed can be controlled by changing the network topology. Furthermore, high parallelism is can be realized by assigning PSO to single processor. The stability condition analysis and performance of PSON are shown.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E98-A No.8 pp.1777-1786
- Publication Date
- 2015/08/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1587/transfun.E98.A.1777
- Type of Manuscript
- PAPER
- Category
- Nonlinear Problems
Authors
Tomoyuki SASAKI
Tokyo City University
Hidehiro NAKANO
Tokyo City University
Arata MIYAUCHI
Tokyo City University
Akira TAGUCHI
Tokyo City University
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Tomoyuki SASAKI, Hidehiro NAKANO, Arata MIYAUCHI, Akira TAGUCHI, "Improvement of the Solving Performance by the Networking of Particle Swarm Optimization" in IEICE TRANSACTIONS on Fundamentals,
vol. E98-A, no. 8, pp. 1777-1786, August 2015, doi: 10.1587/transfun.E98.A.1777.
Abstract: This paper presents a particle swarm optimization network (PSON) to improve the search capability of PSO. In PSON, multi-PSOs are connected for the purpose of communication. A variety of network topology can be realized by varying the number of connected PSOs of each PSO. The solving performance and convergence speed can be controlled by changing the network topology. Furthermore, high parallelism is can be realized by assigning PSO to single processor. The stability condition analysis and performance of PSON are shown.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E98.A.1777/_p
Copy
@ARTICLE{e98-a_8_1777,
author={Tomoyuki SASAKI, Hidehiro NAKANO, Arata MIYAUCHI, Akira TAGUCHI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Improvement of the Solving Performance by the Networking of Particle Swarm Optimization},
year={2015},
volume={E98-A},
number={8},
pages={1777-1786},
abstract={This paper presents a particle swarm optimization network (PSON) to improve the search capability of PSO. In PSON, multi-PSOs are connected for the purpose of communication. A variety of network topology can be realized by varying the number of connected PSOs of each PSO. The solving performance and convergence speed can be controlled by changing the network topology. Furthermore, high parallelism is can be realized by assigning PSO to single processor. The stability condition analysis and performance of PSON are shown.},
keywords={},
doi={10.1587/transfun.E98.A.1777},
ISSN={1745-1337},
month={August},}
Copy
TY - JOUR
TI - Improvement of the Solving Performance by the Networking of Particle Swarm Optimization
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1777
EP - 1786
AU - Tomoyuki SASAKI
AU - Hidehiro NAKANO
AU - Arata MIYAUCHI
AU - Akira TAGUCHI
PY - 2015
DO - 10.1587/transfun.E98.A.1777
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E98-A
IS - 8
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - August 2015
AB - This paper presents a particle swarm optimization network (PSON) to improve the search capability of PSO. In PSON, multi-PSOs are connected for the purpose of communication. A variety of network topology can be realized by varying the number of connected PSOs of each PSO. The solving performance and convergence speed can be controlled by changing the network topology. Furthermore, high parallelism is can be realized by assigning PSO to single processor. The stability condition analysis and performance of PSON are shown.
ER -
English
