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| Presentation | 2017-03-14 10:00 Search Capability of DPSO with Dynamically Varying Gain-Parameter Nobuaki Hashimoto, Masato Kaneko, Toshiya Iwai (Nihon Univ.)  NLP2016-106 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Discrete Particle Swarm Optimization(DPSO) is a metaheuristics that is improved to apply PSO to the discrete optimization problem. Although the update rule of both particle position and velocity for DPSO is formally represented by difference equations of motion of the particle, the dimensional component of the velocity is connected by a probability of the value that its corresponding component of the position vector takes. In this study, introducing gain parameter β in the sigmoid function to control the degree of uncertainty of the probability in the update rule, we numerically investigate the relation between β and the global search capability and whether time scheduling of β improves search performance. Results of our numerical simulation show as follows: (i) the global search capability increases with decreasing the value of β, (ii) in the case of time scheduling function of β, temporally increasing functions β(t) show the large search capability in comparison with decreasing functions, (iii) as compared between properties of search processes for the temporally constant β and the exponentially increasing downward convex function β(t), β(t) realizes search processes with good balance between the ability to search better solutions and the search velocity. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Particle Swarm Optimization / Discrete Particle Swarm Optimization / sigmoid function / time scheduling / search capability / knapsack problem / / | |
| Reference Info. | IEICE Tech. Rep., vol. 116, no. 523, NLP2016-106, pp. 1-6, March 2017. | |
| Paper # | NLP2016-106 | |
| Date of Issue | 2017-03-07 (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) | |
| Download PDF | NLP2016-106 |
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| Conference Information | |
| Committee | NLP |
| Conference Date | 2017-03-14 - 2017-03-15 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nebuta Museum Warasse |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | NLP |
| Conference Code | 2017-03-NLP |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Search Capability of DPSO with Dynamically Varying Gain-Parameter |
| Sub Title (in English) | |
| Keyword(1) | Particle Swarm Optimization |
| Keyword(2) | Discrete Particle Swarm Optimization |
| Keyword(3) | sigmoid function |
| Keyword(4) | time scheduling |
| Keyword(5) | search capability |
| Keyword(6) | knapsack problem |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Nobuaki Hashimoto |
| 1st Author's Affiliation | Nihon University (Nihon Univ.) |
| 2nd Author's Name | Masato Kaneko |
| 2nd Author's Affiliation | Nihon University (Nihon Univ.) |
| 3rd Author's Name | Toshiya Iwai |
| 3rd Author's Affiliation | Nihon University (Nihon Univ.) |
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| Speaker | Author-1 |
| Date Time | 2017-03-14 10:00:00 |
| Presentation Time | 25 minutes |
| Registration for | NLP |
| Paper # | NLP2016-106 |
| Volume (vol) | vol.116 |
| Number (no) | no.523 |
| Page | pp.1-6 |
| #Pages | 6 |
| Date of Issue | 2017-03-07 (NLP) |
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