| id |
cf2017_667 |
| authors |
Cichocka, Judyta; Migalska, Agata; Browne, Will N.; Rodriguez, Edgar |
| year |
2017 |
| title |
SILVEREYE– the implementation of Particle Swarm Optimization algorithm in a design optimization tool |
| source |
Gülen Çagdas, Mine Özkar, Leman F. Gül and Ethem Gürer (Eds.) Future Trajectories of Computation in Design [17th International Conference, CAAD Futures 2017, Proceedings / ISBN 978-975-561-482-3] Istanbul, Turkey, July 12-14, 2017, p. 667. |
| summary |
Engineers and architects are now turning to use computational aids in order to analyze and solve complex design problems. Most of these problems can be handled by techniques that exploit Evolutionary Computation (EC). However existing EC techniques are slow [8] and hard to understand, thus disengaging the user. Swarm Intelligence (SI) relies on social interaction, of which humans have a natural understanding, as opposed to the more abstract concept of evolutionary change. The main aim of this research is to introduce a new solver Silvereye, which implements Particle Swarm Optimization (PSO) in the Grasshopper framework, as the algorithm is hypothesized to be fast and intuitive. The second objective is to test if SI is able to solve complex design problems faster than ECbased solvers. Experimental results on a complex, single-objective high-dimensional benchmark problem of roof geometry optimization provide statistically significant evidence of computational inexpensiveness of the introduced tool. |
| keywords |
Architectural Design Optimization (ADO), Particle Swarm Optimization (PSO), Swarm Intelligence (SI), Evolutionary Computation (EC), Structural Optimization |
| series |
CAAD Futures |
| email |
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| full text |
 file.pdf (162,177 bytes) |
| references |
Content-type: text/plain
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| last changed |
2017/12/01 14:38 |
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