| id |
ecaadesigradi2019_456 |
| authors |
Pereira, In?s, Belém, Catarina and Leit?o, António |
| year |
2019 |
| title |
Optimizing Exhibition Spaces - A Multi-Objective Approach |
| doi |
https://doi.org/10.52842/conf.ecaade.2019.3.053
|
| source |
Sousa, JP, Xavier, JP and Castro Henriques, G (eds.), Architecture in the Age of the 4th Industrial Revolution - Proceedings of the 37th eCAADe and 23rd SIGraDi Conference - Volume 3, University of Porto, Porto, Portugal, 11-13 September 2019, pp. 53-62 |
| summary |
Nowadays, there is a widespread awareness towards environmental issues. This is already visible in architecture by the increasing number of analysis tools that evaluate different performance criteria. However, the application of these tools is usually restricted to the final design stages, conditioning the implementation of design changes. Performance-Based Design (PBD) is an approach that addresses this limitation. Through PBD, architects integrate analysis tools since early design stages to make informed decisions regarding the performance of their designs. Since the success of PBD highly depends on the number of evaluations that can be performed, these approaches usually end up benefiting from Parametric Models (PMs), which facilitate the generation of a wide range of design variations, by simply changing the values of the parameters. Furthermore, in order to more efficiently achieve a PBD approach, architects can take advantage of the combination between PMs, analysis tools, and optimization processes. In this paper, we explore this combination to optimize an exhibition space regarding its daylight performance and the material cost of the new elements intended for that space. |
| keywords |
Environmental Design; Algorithmic Design and Analysis; Performance-Based Design; Multi-Objective Optimization; Daylight Optimization |
| series |
eCAADeSIGraDi |
| email |
ines.pereira@tecnico.ulisboa.pt |
| full text |
 file.pdf (2,001,260 bytes) |
| references |
Content-type: text/plain
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| last changed |
2022/06/07 08:00 |
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