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Paper Abstract and Keywords
Presentation 2026-07-09 14:15
Acceleration of alpha-GPSA by Reducing the Computational Cost of Gravitational Vector Calculation
Daiki Kurata, Yoshikazu Yamanaka, Katsutoshi Yoshida (Utsunomiya Univ.) NLP2026-29
Abstract (in Japanese) (See Japanese page) 
(in English) In adaptive Gravitational Particle Swarm Algorithm ($alpha$GPSA), a multimodal optimization (MMO) algorithm developed by our group, the computational load of gravitational vector calculation increases as the number of particles increases,
resulting in a longer execution time. This is because the conventional $alpha$GPSA calculates gravitational vectors by referring to all particles. Therefore,
this study proposes a fast $alpha$GPSA in which each particle calculates the gravitational vector by referring not to all other particles but to $M$ randomly selected particles. In the numerical experiments,
the execution times of the conventional and proposed methods were compared using the CEC2013 benchmark function $f_1$, and the proposed method was confirmed to reduce the execution time compared with the conventional method. In addition,
the Peak Ratio (PR) was evaluated using seven functions from CEC2013. The results showed that the proposed method maintained or improved the ability to find multiple global optima for many benchmark functions,
while performance degradation was observed for some benchmark functions.
This study demonstrates that limiting the targets of gravitational vector calculation is effective for accelerating $alpha$GPSA and suggests the potential of a search method with a low computational load for MMO problems.
Keyword (in Japanese) (See Japanese page) 
(in English) $alpha$GPSA / MMO / benchmark function / / / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 94, NLP2026-29, pp. 19-23, July 2026.
Paper # NLP2026-29 
Date of Issue 2026-07-02 (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)
Download PDF NLP2026-29

Conference Information
Committee NLP  
Conference Date 2026-07-09 - 2026-07-10 
Place (in Japanese) (See Japanese page) 
Place (in English) Toki Koryu Kaikan (Sado) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Nonlinear problems, etc. 
Paper Information
Registration To NLP 
Conference Code 2026-07-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Acceleration of alpha-GPSA by Reducing the Computational Cost of Gravitational Vector Calculation 
Sub Title (in English)  
Keyword(1) $alpha$GPSA  
Keyword(2) MMO  
Keyword(3) benchmark function  
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1st Author's Name Daiki Kurata  
1st Author's Affiliation Utsunomiya University (Utsunomiya Univ.)
2nd Author's Name Yoshikazu Yamanaka  
2nd Author's Affiliation Utsunomiya University (Utsunomiya Univ.)
3rd Author's Name Katsutoshi Yoshida  
3rd Author's Affiliation Utsunomiya University (Utsunomiya Univ.)
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Speaker Author-1 
Date Time 2026-07-09 14:15:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2026-29 
Volume (vol) vol.126 
Number (no) no.94 
Page pp.19-23 
#Pages 5 
Date of Issue 2026-07-02 (NLP) 

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