Genetic Algorithm Site Layout Optimization
Genetic Algorithm Site Layout Optimization is a computational method that belongs to the class of evolutionary optimization techniques, distinguished by its use of genetic algorithm principles—such as selection, crossover, and mutation—to systematically generate and refine site layout configurations that optimize spatial efficiency, resource accessibility, and operational safety in construction and industrial engineering projects.
71
Publications
5.3K
Citations
174
Authors
97
Institutions
Publications per year
2017–2026
15
Parents
71
1–5 of 71
174
4
h-index
3
h-index
3
h-index
3
h-index
3
h-index
1–5 of 174
97

City University of Hong Kong
Hong Kong, Hong Kong
6 h-index
17 publications
1.4K citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
7 publications
495 citations

University of Waterloo
Waterloo, Canada
3 h-index
5 publications
535 citations

University of Alberta
Edmonton, Canada
3 h-index
4 publications
170 citations

Cairo University
Giza, Egypt
3 h-index
8 publications
1.2K citations

Hong Kong Polytechnic University
Hong Kong, Hong Kong
3 h-index
5 publications
236 citations

University of Twente
Enschede, The Netherlands
2 h-index
2 publications
194 citations
Canadian Natural Resources
Calgary, Canada
2 h-index
2 publications
130 citations
1–8 of 97
9 publications · 801 citations
9
h-index
8 publications · 682 citations
8
h-index
4 publications · 1.3K citations
4
h-index
3 publications · 364 citations
3
h-index
3 publications · 175 citations
3
h-index
1–5