Generative Design for project optimization (S).

The present work concerns the applications of Generative Design in the Architectural sector: this represents an iterative process that involves an algorithm for the generation of a few outputs to satisfy certain constraints. Generative Design can offer advantages to traditional building design and the urban planning processes, given its capability to manage complexity by optimizing specifically preselected criteria while still at the drafting stage. The case study is a building currently under construction at the Valladolid Campus, and the objective is to analyse whether or not its design process has been exhaustive. The first step was to define inputs and variables depending on the ultimate goals. Successively it was time to set the boundaries for the outputs in terms of the different displayable and measurable solutions. Then the last step was to select the optimal solution. The tools employed are Formit for basic modelling, Revit for BIM modelling, Dynamo for visual programming, using graphs and nodes customizable through Python scripts. Specifically, for the Generative Design part and results displaying, Refinery used an Autodesk beta version software. Refinery implements a genetic algorithm with an NSGA-II optimization, a meta-heuristic algorithm for multi-objective optimization. Once the optimal solution has been determined, it is possible to import the results back into a Dynamo for Revit environment to complete the BIM modeling according to the Level of Geometry (LOG) and Information (LOI) required. Generative Design; optimization; BIM; Parametric Design;