Design Variant Generation

Design Variant Generation is a computational method within interactive generative design that systematically produces distinct, feasible design alternatives by exploring and differentiating a design space according to specified parameters, constraints, and generative rules.

46

Publications

1.9K

Citations

125

Authors

50

Institutions

Publications per year

2017–2026

17

Authors

125

  1. RB
    Robert B. Stone

    Missouri University of Science and Technology, United States

    5 publications · 363 citations

    5

    h-index

  2. DA
    Daniel A. McAdams

    Texas A&M University, United States

    3 publications · 274 citations

    3

    h-index

  3. MI
    Matthew I. Campbell

    The University of Texas at Austin, United States

    3 publications · 228 citations

    3

    h-index

  4. TK
    Tolga Kurtoglu

    Ames Research Center, United States

    3 publications · 228 citations

    3

    h-index

  5. AZ
    Allan Zhao

    Massachusetts Institute of Technology, United States

    2 publications · 55 citations

    2

    h-index

1–5 of 125

Venues

  1. Journal of Computing and Information Science in Engineering

    JCISE · 4 publications · 179 citations

    4

    h-index

  2. Research in Engineering Design

    3 publications · 67 citations

    3

    h-index

  3. arXiv (Cornell University)

    Repository · 2 publications · 38 citations

    2

    h-index

  4. Computer

    1 publications · 74 citations

    1

    h-index

  5. Proceedings of the Genetic and Evolutionary Computation Conference

    Conference · 1 publications · 55 citations

    1

    h-index

1–5