Learning the optimal product design through history

    研究成果: Conference contribution

    4 被引用数 (Scopus)

    抄録

    The search for novel and high-performing product designs is a ubiquitous problem in science and engineering: aided by advances in optimization methods the conventional approaches usually optimize a (multi) objective function using simulations followed by experiments. However, in some scenarios such as vehicle layout design, simulations and experiments are restrictive, inaccurate and expensive. In this paper, we propose an alternative approach to search for novel and highperforming product designs by optimizing not only a proposed novelty metric, but also a performance function learned from historical data. Computational experiments using more than twenty thousand vehicle models over the last thirty years shows the usefulness and promising results for a wider set of design engineering problems.

    本文言語English
    ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    出版社Springer Verlag
    ページ382-389
    ページ数8
    9489
    ISBN(印刷版)9783319265315
    DOI
    出版ステータスPublished - 2015
    イベント22nd International Conference on Neural Information Processing, ICONIP 2015 - Istanbul, Turkey
    継続期間: 2015 11 92015 11 12

    出版物シリーズ

    名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    9489
    ISSN(印刷版)03029743
    ISSN(電子版)16113349

    Other

    Other22nd International Conference on Neural Information Processing, ICONIP 2015
    CountryTurkey
    CityIstanbul
    Period15/11/915/11/12

    ASJC Scopus subject areas

    • Computer Science(all)
    • Theoretical Computer Science

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