Generative Architectural Form Finding

Generative Architectural Form Finding is a computational design methodology within evolutionary architecture that systematically generates and optimizes architectural forms through algorithmic processes informed by performance criteria, environmental constraints, and generative rules distinct from manual or intuitive design approaches.

8

Publications

220

Citations

16

Authors

5

Institutions

Publications per year

2017–2026

3

Authors

16

  1. YJ
    Yasha J. Grobman

    Technion – Israel Institute of Technology, Israel

    1 publications · 10 citations

    1

    h-index

  2. IK
    Immanuel Koh

    Zhejiang University, China

    1 publications · 11 citations

    1

    h-index

  3. MT
    Martha Tsigkari

    University College London, United Kingdom

    1 publications · 16 citations

    1

    h-index

  4. JV
    Jeroen van Ameijde

    Utrecht University, Netherlands

    1 publications · 33 citations

    1

    h-index

  5. AJ
    Anna Jaruga-Rozdolska

    1 publications · 102 citations

    1

    h-index

1–5 of 16

Venues

  1. Architectural Design

    AD · 2 publications · 28 citations

    2

    h-index

  2. Annual Simulation Symposium

    Conference · 1 publications · 16 citations

    1

    h-index

  3. Frontiers of Architectural Research

    1 publications · 33 citations

    1

    h-index

  4. 1

    h-index

  5. eCAADe proceedings

    2 publications · 22 citations

    1

    h-index

1–5