This paper examines the applicability of a Multi Objective Optimization (MOO) methodology within a parametric design setup. The primary focus of MOO is to facilitate early stage decision making in professional High Performance Building (HPB) practice. With environmental variables and objectives stemming from all design disciplines, there is a need for designers and engineers to work together to capitalize on their varied expertise and achieve efficiencies in HPB design optimization. This paper outlines two experiments carried out using the Octopus plugin, which is a MOO solver, within the Grasshopper (GH) parametric design interface. The findings show promising outcomes, highlight potential opportunities, and identify limitations of the proposed methodology.
| File Size : | 1
file
, 2.6 MB |
| Note : | This product is unavailable in Russia, Belarus |
| Number of Pages : | 8 |
| Product Code(s) : | D-BSC18-C088 |
| Published : | 2018 |
| Units of Measure : | Dual |
