CGoDesign_A modular generative design framework for mass-customization and optimization in architectural design
In this presentation, we demonstrate a modular generative design framework for design processes in the built environment that provides for the unification of participatory design and optimization to achieve mass-customization and evidence-based design. The paper articulates this framework mathematically as three meta procedures framing the typical design problems as multi-dimensional, multi-criteria, multi-actor, and multi-value decision-making problems: 1) space-planning, 2) configuring, and 3) shaping; structured as to the abstraction hierarchy of the chain of decisions in design processes. These formulations allow for applying various problem-solving approaches ranging from mathematical derivation & artificial intelligence to gamified play & score mechanisms and grammatical exploration. The paper presents a general schema of the framework; elaborates on the mathematical formulation of its meta procedures; presents a spectrum of approaches for navigating solution spaces; discusses the specifics of spatial simulations for ex-ante evaluation of design alternatives. The ultimate contribution of this paper is laying the foundation of comprehensive Spatial Decision Support Systems (SDSS) for built environment design processes.