Paper Abstract and Keywords |
Presentation |
2016-12-13 10:30
Particle Swarm Optimization with Refractory Period of Particle Velocity Update Yuki Nagano, Hideharu Toda (Chukyo Univ.), Masatoshi Sato (Tokyo Metropolitan Univ.), Hisashi Aomori (Chukyo Univ.) NLP2016-94 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Particle Swarm Optimization (PSO) is one of the metaheuristics where each particles in a swarm searches an optimal solution of the given objective function.
Because of the succinctness of its algorithm, the implementation cost of the PSO in software and hardware is very low, and it is expected to be applied in various problems.
However, the global optimization of multimodal objective functions utilizes the PSO is very difficult, due to the fact that particles are easy to fall into local optimums in them.
In this paper, to deal with this difficulty, the PSO with refractory period of particle velocity update is proposed.
In the event of the particle velocity update, if a particle is located near the global best called gbest, velocity of particle will be lost.
To prevent this velocity lost, we give refractory periods for a particle. In refractory periods, a particle keeps its last velocity.
In order to comfirm the effectiveness of the proposed method, the proposed method was applied to various benchmark functions.
The experimental results showed that the proposed method has a high search performance in the high dimensonal multimodal functions compared with conventional methods. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Particle Swarm Optimization / Refractory Period / Search Perfomance / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 116, no. 353, NLP2016-94, pp. 55-59, Dec. 2016. |
Paper # |
NLP2016-94 |
Date of Issue |
2016-12-05 (NLP) |
ISSN |
Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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NLP2016-94 |
Conference Information |
Committee |
NLP |
Conference Date |
2016-12-12 - 2016-12-13 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Chukyo Univ. |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
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Paper Information |
Registration To |
NLP |
Conference Code |
2016-12-NLP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Particle Swarm Optimization with Refractory Period of Particle Velocity Update |
Sub Title (in English) |
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Keyword(1) |
Particle Swarm Optimization |
Keyword(2) |
Refractory Period |
Keyword(3) |
Search Perfomance |
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1st Author's Name |
Yuki Nagano |
1st Author's Affiliation |
Chukyo University (Chukyo Univ.) |
2nd Author's Name |
Hideharu Toda |
2nd Author's Affiliation |
Chukyo University (Chukyo Univ.) |
3rd Author's Name |
Masatoshi Sato |
3rd Author's Affiliation |
Tokyo Metropolitan University (Tokyo Metropolitan Univ.) |
4th Author's Name |
Hisashi Aomori |
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Chukyo University (Chukyo Univ.) |
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Speaker |
Author-1 |
Date Time |
2016-12-13 10:30:00 |
Presentation Time |
25 minutes |
Registration for |
NLP |
Paper # |
NLP2016-94 |
Volume (vol) |
vol.116 |
Number (no) |
no.353 |
Page |
pp.55-59 |
#Pages |
5 |
Date of Issue |
2016-12-05 (NLP) |
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