Performance analysis of localization strategy for island model genetic algorithm

Alfian Akbar Gozali, Shigeru Fujimura

研究成果: Conference contribution

2 被引用数 (Scopus)

抄録

Genetic algorithm (GA) is one of the standard solutions to solve many optimization problems. One of a GA type used for solving a case is island model GA (IMGA). Localization strategy is a brand-new feature for IMGA to better preserves its diversity. In the previous research, localization strategy could carry out 3SAT problem almost perfectly. In this study, the proposed feature is aimed to solve real parameter single objective computationally expensive optimization problems. Differ with an issue in previous research which has a prior knowledge and binary, the computationally expensive optimization has not any prior knowledge and floating type problem. Therefore, the localization strategy and its GA cores must adapt. The primary goal of this research is to analyze further the localization strategy for IMGA's performance. The experiments show that the new feature is successfully modified to meet the new requirement. Localization strategy for IMGA can solve all computationally expensive functions consistently. Moreover, this new feature could make IMGA reaches leading ratio 0.47 among other current solvers.

元の言語English
ホスト出版物のタイトルProceedings - 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2017
編集者Hiroaki Hirata, Nomiya Hiroki, Teruhisa Hochin
出版者Institute of Electrical and Electronics Engineers Inc.
ページ327-332
ページ数6
ISBN(電子版)9781509055043
DOI
出版物ステータスPublished - 2017 8 29
イベント18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2017 - Kanazawa, Japan
継続期間: 2017 6 262017 6 28

出版物シリーズ

名前Proceedings - 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2017

Other

Other18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2017
Japan
Kanazawa
期間17/6/2617/6/28

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture

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