Generative Planning

Generative Design

Generative Design


{Simulation-Driven, Gradual, Transparent, Explainable, and Reproduceable}

‘Combinatorial Generation’


{a Navigable Catalogue of Valid/Optimal Design Alternatives}

Architectural Design & Planning Problems typically involve challenging requirements, constraints, and competing goals pertaining to social, economic, and environmental values as well as human factors, spatial ergonomics, and comfort that bring about both physical and human complexities. Furthermore, balancing the suitability of solutions with respect to the expected operational functionality of spatial configurations & forms and their adaptability towards future requirements are often challenging. A particular area of attention, where such design problems culminate in complexity and count at a considerable scale, is qualitative mass-customization of housing. Being able to guarantee the quality of design alternatives while satisfying such a complex plethora of demands and considerations necessitates a transparent, explainable, and reproducible scientific approach capable of understanding the dynamics of physical and human complexity of design decision-making. Research and Development in “Generative Systems & Sciences'' revolves around mathematically or computationally modelling the human-physical complexity of design & spatial decision-making as well as promoting the idea of scientific design as open and modular participatory processes of scientific discovery and innovation. The general quest of this line of inquiry is to develop interactive/gamified spatial, multi-criteria, and multi-actor Generative Design Decision-Support Systems to contribute to the open-source development of equitable, circular, and sustainable buildings and cities. Generative Sciences, as interdisciplinary approaches based on Network Models, are suited for simulating the interactions of intricate webs of inter-related spaces, criteria, actors, and values; and as such, provide a basis for understanding and controlling the formation of patterns and emergence of collective decisions in Digital Twins. Generative Systems, as simulation systems (possibly human-machine hybrids), can provide mechanisms for logical transitions from design requirements, considerations, and values to suitable and adaptable design alternatives.
Image Credit: Definition, Scope, and focal areas of Innovation, Research, and Development in Generative Design using Generative Sciences (Methodologies) and Generative Systems (Technologies) by Pirouz Nourian
"A form is only a single solution to a problem that could have had many more solutions. The problem is thus more interesting that the solution because it has a richer information content."
Generative Design processes are simulation-driven and topological/configurative optimization/adaptation processes for combinatorial generation of navigable catalogue of valid/optimal design alternatives. Generative Sciences are interdisciplinary approaches to the study of Complex Systems based on Network Models, Dynamical Systems, Agent-Based Models, Stochastics, Nature-Inspired Computing, and Partial Differential Equations that focus on the emergence of patterns and genesis of Collective Intelligence (Natural + Artificial Intelligence) in Self-Organized Systems.
Image Credit: Genesis Lab
Participatory Generative Design Research Methodology
Image Credit: Genesis Lab, Generative Design contributions to sustainability