Genetic Programming For Design
Genetic Programming for Design is a computational methodology within evolutionary design that employs principles of genetic algorithms—such as mutation, crossover, and selection—to autonomously generate and optimize design solutions through iterative improvement of encoded design representations.
347
Publications
15.5K
Citations
817
Authors
360
Institutions
Publications per year
2017–2026
73
Parents
347
1–5 of 347
817
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h-index
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h-index
9
h-index
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h-index
9
h-index
1–5 of 817
360
Stanford University
Stanford, United States
14 h-index
24 publications
1.7K citations

University of Zagreb
Zagreb, Croatia
10 h-index
17 publications
539 citations
Michigan State University
East Lansing, United States
10 h-index
25 publications
1.3K citations
Gaziantep University
Gaziantep, Türkiye
9 h-index
22 publications
2.4K citations

Victoria University of Wellington
Wellington, New Zealand
8 h-index
16 publications
1.3K citations

University of York
York, United Kingdom
8 h-index
11 publications
303 citations
Nanyang Technological University
Singapore, Singapore
7 h-index
14 publications
647 citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
7 h-index
13 publications
488 citations
1–8 of 360
12 publications · 576 citations
12
h-index
12 publications · 1.5K citations
11
h-index
11 publications · 518 citations
11
h-index
11 publications · 744 citations
11
h-index
5 publications · 93 citations
5
h-index
1–5