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Paper Abstract and Keywords
Presentation 2023-01-28 09:50
Performance evaluation of success-history based parameter adaptation for differential evolution for multi-objective optimization problems
Yusuke Matsuzaki, Jun Adachi, Takafumi Matsuura, Takayuki Kimura (NIT) NLP2022-81 NC2022-65
Abstract (in Japanese) (See Japanese page) 
(in English) A Multi-objective Optimization Problems (MOPs) is a problem for simultaneously optimizing objective functions with different evaluation criteria. The Cooperative Multi-Objective Differential Evolution (CMODE) method that uses Adaptive parameter control Differential Evolution (JADE) method, which is a single objective optimization method, has been proposed for solving the MOPs. However, the CMODE shows poor performance because the Janez’s DE (jDE), which aims to obtain good Pareto solution, randomly selects solutions for the crossover operations. In this study, we propose a new multi-objective optimization method that uses Success History Based Parameter Adaptitaion for Differential Evolution (SHADE), which has an excellent performance for single-objective optimization methods, based on the CMODE method. In addition, we introduce the truncation method, and the improved mutation method of JADE to enhance solution quality of the Pareto front. From the numerical experiment, we confirmed that our proposed method improves search solutions, effectively.
Keyword (in Japanese) (See Japanese page) 
(in English) Multi-objective Optimization Problem / Evolutionary Algorithms / Differential Evolution / CMODE / SHADE / / /  
Reference Info. IEICE Tech. Rep., vol. 122, no. 373, NLP2022-81, pp. 1-6, Jan. 2023.
Paper # NLP2022-81 
Date of Issue 2023-01-21 (NLP, NC) 
ISSN Online edition: ISSN 2432-6380
Copyright
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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 NLP2022-81 NC2022-65

Conference Information
Committee NC NLP  
Conference Date 2023-01-28 - 2023-01-29 
Place (in Japanese) (See Japanese page) 
Place (in English) Future University Hakodate 
Topics (in Japanese) (See Japanese page) 
Topics (in English) NC, NLP, etc. 
Paper Information
Registration To NLP 
Conference Code 2023-01-NC-NLP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Performance evaluation of success-history based parameter adaptation for differential evolution for multi-objective optimization problems 
Sub Title (in English)  
Keyword(1) Multi-objective Optimization Problem  
Keyword(2) Evolutionary Algorithms  
Keyword(3) Differential Evolution  
Keyword(4) CMODE  
Keyword(5) SHADE  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Yusuke Matsuzaki  
1st Author's Affiliation Nippon Institute of technology (NIT)
2nd Author's Name Jun Adachi  
2nd Author's Affiliation Nippon Institute of technology (NIT)
3rd Author's Name Takafumi Matsuura  
3rd Author's Affiliation Nippon Institute of technology (NIT)
4th Author's Name Takayuki Kimura  
4th Author's Affiliation Nippon Institute of technology (NIT)
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Speaker Author-1 
Date Time 2023-01-28 09:50:00 
Presentation Time 25 minutes 
Registration for NLP 
Paper # NLP2022-81, NC2022-65 
Volume (vol) vol.122 
Number (no) no.373(NLP), no.374(NC) 
Page pp.1-6 
#Pages 6 
Date of Issue 2023-01-21 (NLP, NC) 

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