| id |
cf2019_008 |
| authors |
Han, Zhen; Ning Cao, Gang Liu and Wei Yan |
| year |
2019 |
| title |
MOPSO for BIM: A Multi-Objective Optimization Tool Using Particle Swarm Optimization Algorithm on a BIMbased Visual Programming Platform |
| source |
Ji-Hyun Lee (Eds.) "Hello, Culture!" [18th International Conference, CAAD Futures 2019, Proceedings / ISBN 978-89-89453-05-5] Daejeon, Korea, pp. 39-51 |
| summary |
With the increasing applications of computational methods in the field of design optimization, intelligent metaheuristic algorithms are playing a more important role in building performance optimization. To enable the integration of optimization algorithms with Building Information Modeling (BIM), this research implemented the Particle Swarm Optimization (PSO) algorithm on Revit + Dynamo, which is a parametric BIM platform. A MultiObjective PSO (MOPSO) Solver has been developed in Dynamo using MATLAB and C# programming languages. The methodology of the research and the validation studies are presented in the paper. The validation studies prove the effectiveness of the MOPSO Solver for both standard optimization test functions and an optimization example of a simplified building design. |
| keywords |
Particle Swarm Optimization, BIM, multi-objective optimization, visual programming |
| series |
CAAD Futures |
| email |
|
| full text |
 file.pdf (956,268 bytes) |
| references |
Content-type: text/plain
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| last changed |
2019/07/29 14:08 |
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