Local Information of Fitness Landscape Obtained by Paired Comparison-Based Memetic Search for Interactive Differential Evolution - Collections | Kyushu University Library

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＜conference paper＞
Local Information of Fitness Landscape Obtained by Paired Comparison-Based Memetic Search for Interactive Differential Evolution

Creator	Creator Name Pei, Yan 裴, 岩 Affiliation Affiliation Name Computer Science Division, Universally of Aizu 会津大学コンピュータサイエンス部門
Creator	Author PID K002333 0000-0002-1431-9472 Creator Name Takagi, Hideyuki 髙木, 英行 Affiliation Affiliation Name Faculty of Design, Kyushu University 九州大学大学院芸術工学研究院
Language	English
Publisher	IEEE
Date	2015-05-25
Source Title	IEEE Congress on Evolutionary Computation
Vol	2015
First Page	2215
Last Page	2221
Publication Type	Accepted Manuscript
Access Rights	open access
Related DOI	Proceedings, 2015 IEEE Congress on Evolutionary Computation (CEC)
Related DOI	https://doi.org/10.1109/CEC.2015.7257158
Related URI	https://doi.org/10.1109/CEC.2015.7257158
Relation	Proceedings, 2015 IEEE Congress on Evolutionary Computation (CEC)
Relation	https://doi.org/10.1109/CEC.2015.7257158
Abstract	We propose a triple comparison-based interactive differential evolution (IDE) algorithm. The comparison of target vector and trail vector supports a local fitness landscape for IDE algorithm to conduc...t a memetic search. Besides target vector and trail vector in canonical IDE algorithm framework, we conduct a memetic search around whichever is the vector with better fitness. We use a random number from a normal distribution generator or a uniform distribution generator to perturb the vector for generating a third vector. By comparing the target vector, the trail vector and the third vector, we implement a triple comparison mechanism in IDE algorithm. A Gaussian mixture model is applied as a pseudo IDE user in our evaluation. We compare our proposal with canonical IDE and triple comparison-based IDE implemented by opposite-based learning, and apply several statistical test to investigate the significance of our proposed algorithm. From the evaluation results, our proposed triple comparison-based IDE algorithm shows significantly better performance optimization. We also investigate potential issues arising from our proposal, and discuss some open topics and future opportunities.show more
Table of Contents	Ⅰ.INTRODUCTION Ⅱ.INTERACTIVE DIFFERENTIAL EVOLUTION AND MULTIPLE COMPARISON MECHANISM FOR HUMAN EVALUATION Ⅲ.MEMETIC SEARCH IN INTERACTIVE DIFFERENTIAL EVOLUTION FOR IMPLEMENTING A NEW TRIPLE COMPARISON MECHANISM Ⅳ.OPTIMIZATION EVALUATION Ⅴ.DISCUSSION Ⅵ.CONCLUSION AND FUTURE WORK

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Details

Record ID	1808907
Peer-Reviewed	Unrefereed
ISSN	1089-778X
ISBN	978-1-4799-7492-4
DOI	10.1109/CEC.2015.7257158
Notes	2015 IEEE Congress on Evolutionary Computation (CEC) : 25-28 May 2015 : Sendai, Japan
Created Date	2017.06.14
Modified Date	2021.10.06