Generative Design Exploration
Generative Design Exploration is a computational design methodology that systematically generates and evaluates a vast array of design alternatives through algorithmic processes, distinguished by its integration of generative algorithms, performance simulations, and evolutionary principles to autonomously explore and optimize solutions within a defined parameter space.
72
Publications
3.1K
Citations
188
Authors
81
Institutions
Publications per year
2017–2026
50
Parents
72
Deep Generative Design: Integration of Topology Optimization and Generative Models
Sangeun Oh, Yongsu Jung, Seongsin Kim et al. · Journal of Mechanical Design · 2019 · 437 citations · Full text
Justin Matejka, Michael Glueck, Erin Bradner et al. · 2018 · 143 citations
Architecture, Design, Visualization +17
1–5 of 72
188
4
h-index
4
h-index
2
h-index
2
h-index
2
h-index
1–5 of 188
81

Delft University of Technology
Delft, The Netherlands
4 h-index
8 publications
192 citations
Korea Advanced Institute of Science and Technology
Daejeon, South Korea
4 h-index
12 publications
1.2K citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
9 publications
379 citations
University College London
London, United Kingdom
2 h-index
5 publications
72 citations

The University of Sydney
Sydney, Australia
2 h-index
4 publications
142 citations

The Open University
Milton Keynes, United Kingdom
2 h-index
6 publications
180 citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
2 h-index
5 publications
93 citations
The University of Texas at Austin
Austin, United States
2 h-index
4 publications
70 citations
1–8 of 81
8 publications · 647 citations
8
h-index
AIEDAM · 3 publications · 59 citations
3
h-index
IJAC · 3 publications · 43 citations
3
h-index
2 publications · 70 citations
3
h-index
3 publications · 186 citations
3
h-index
1–5