Technical

Computational Design: Data-Driven Architectural Decision Making

Use of parametric modeling and evolutionary algorithms in early design stages. Automatic form optimization based on performance criteria and multivariate analysis processes.

Computational design is a methodology where architectural decisions are supported by data and algorithms as much as intuition and experience. In the traditional design process, a form decision is made, then analyzed. In computational design, analysis determines the form.

REACTO's computational design toolkit, running on Grasshopper / Rhino, includes multi-objective optimization algorithms (NSGA-II, MOGA). In early project stages, the architect defines inputs like site boundaries, zoning conditions, budget, and program. The algorithm generates all possible geometric variations within these constraints and scores each according to criteria like daylight, energy efficiency, visual comfort, and construction cost.

Multivariate analysis is one of the most powerful tools of computational design. A building's facade design is not just an aesthetic decision; it is the optimization of potentially conflicting criteria: energy performance, privacy, daylight efficiency, wind load, and material cost. The most balanced solution set (Pareto frontier) is determined through Pareto optimization.