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Dominance relation‐based genetic algorithm for superior solution set search problem
Author(s) -
Fukushima Ryu,
Wang Hongran,
Tamura Kenichi,
Tsuchiya Junichi,
Yasuda Keiichiro
Publication year - 2019
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22888
Subject(s) - mathematical optimization , set (abstract data type) , relation (database) , genetic algorithm , solution set , algorithm , dominance (genetics) , computer science , search algorithm , local search (optimization) , mathematics , data mining , biochemistry , chemistry , gene , programming language
The superior solution set search problem contains parameters that provide constraints on evaluation value and distance. Therefore, in this article, we propose an evaluation indicator that is inspired by a method based on a dominance relation in multiobjective optimization problems and includes the aforementioned parameters. We also propose a search method based on the genetic algorithm (GA) with this indicator and perform numerical experiments on unique superior solution set search problems. The proposed method finds more superior solutions than the conventional single‐objective optimization method, which confirms its usefulness. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.