| id |
caadria2009_065 |
| authors |
Li, Biao; Rong Li |
| year |
2009 |
| title |
Optimal Organization of Architectural Spaces Based on Genetic Algorithm |
| doi |
https://doi.org/10.52842/conf.caadria.2009.653
|
| source |
Proceedings of the 14th International Conference on Computer Aided Architectural Design Research in Asia / Yunlin (Taiwan) 22-25 April 2009, pp. 653-661 |
| summary |
Genetic algorithms categorized as global search heuristics are search technique of seeking approximate or exact solutions for optimizing problems. Our generative tool named notchSpace starts from a population of randomly generated individuals which rationally subdivide architectural spaces with a low “fitness”. During generations’ evolution, the population is recombined, modified and mutated at a low rate to form new modes of building spatial subdivision; a new population is used in the next iteration. NotchSpace works up a research platform to evolve architectural spaces, and it explores the thinking of translation from computer algorithms to the field of architecture. |
| keywords |
Genetic algorithms; evolutions; fitness; crossover |
| series |
CAADRIA |
| email |
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| full text |
 file.pdf (1,310,645 bytes) |
| references |
Content-type: text/plain
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Grefenstettee, J.J., and Gopal, R. (1985)
 Genetic Algorithms for the Salesman Problem
, Proceedings of the First International Conference on Genetic Algorithms, pp. 160-168
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Holland, J. (1992)
Genetic Algorithms
, Scientific American, July, 66-72
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Narahara, T. and Terzidis, K. (2006)
Multiple-constraint Genetic Algorithm in Housing Design
, "Synthetic Landscapes, in Proceedings of 25th Annual Conference of the Association for Computer-Aided Design in Architecture, pp. 418-425. "
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| last changed |
2022/06/07 07:59 |
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