Paper Abstract and Keywords |
Presentation |
2021-12-18 13:00
A Study on the Solution Finding Ability of PSO Considering Micro Perturbations Riku Takato, Kenya Jin'no (Tokyo City University) NLP2021-61 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The Particle Swarm Optimization (PSO) method is one of the heuristic methods to search for the optimal value of a black box objective function.
While PSO is less prone to local minima than the gradient method, it has the problem that over time, the particles converge before finding the ideal solution.
To solve this problem, we propose PSO, which adds a small perturbation to the positional information of each particle.
Numerical simulations show that the solution search performance is improved for almost all the benchmark functions with a small number of particles. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
PSO / black box / optimization / perturbations / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 121, no. 307, NLP2021-61, pp. 82-85, Dec. 2021. |
Paper # |
NLP2021-61 |
Date of Issue |
2021-12-10 (NLP) |
ISSN |
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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NLP2021-61 |
Conference Information |
Committee |
NLP |
Conference Date |
2021-12-17 - 2021-12-18 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
J:COM Horuto Hall OITA |
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(See Japanese page) |
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Paper Information |
Registration To |
NLP |
Conference Code |
2021-12-NLP |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
A Study on the Solution Finding Ability of PSO Considering Micro Perturbations |
Sub Title (in English) |
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PSO |
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black box |
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optimization |
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perturbations |
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1st Author's Name |
Riku Takato |
1st Author's Affiliation |
Tokyo City University (Tokyo City University) |
2nd Author's Name |
Kenya Jin'no |
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Tokyo City University (Tokyo City University) |
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Speaker |
Author-1 |
Date Time |
2021-12-18 13:00:00 |
Presentation Time |
25 minutes |
Registration for |
NLP |
Paper # |
NLP2021-61 |
Volume (vol) |
vol.121 |
Number (no) |
no.307 |
Page |
pp.82-85 |
#Pages |
4 |
Date of Issue |
2021-12-10 (NLP) |
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