Local information of fitness landscape obtained by paired comparison-based memetic search for interactive differential evolution

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

3 被引用数 (Scopus)

抄録

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 conduct 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 comparisonbased IDE implemented by opposite-based learning, and apply several statistical tests 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.

本文言語英語
ホスト出版物のタイトル2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ2215-2221
ページ数7
ISBN(電子版)9781479974924
DOI
出版ステータス出版済み - 9 10 2015
イベントIEEE Congress on Evolutionary Computation, CEC 2015 - Sendai, 日本
継続期間: 5 25 20155 28 2015

出版物シリーズ

名前2015 IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings

その他

その他IEEE Congress on Evolutionary Computation, CEC 2015
Country日本
CitySendai
Period5/25/155/28/15

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computational Mathematics

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