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We present 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.

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Our approach to Generative Design converts the problems of design from the geometrical drawing of shapes in a continuous setting to topological decision making about spatial configurations in a discrete setting. The paper presents a comprehensive formulation of the zoning problem as a sub-problem of architectural 3D layout configurations. This formulation focuses on the problem of zoning as a location-allocation problem in the context of Operations Research. Specifically, we propose a methodology for solving this problem by combining a well-known Multi-Criteria Decision-Analysis (MCDA) method called 'Technique for Order of Preference by Similarity to Ideal Solution' (TOPSIS) with a Multi-Agent System (MAS) operating in a discrete design space.

The paper presents open-source computational workflows for assessing the "Exposure to sunlight" and "View out" criteria as defined in the European standard EN 17037 "Daylight in Buildings", issued by the European Committee for Standardization. In addition to these factors, the standard document also addresses daylight provision and protection from glare, both of which fall out of the scope of this paper. The purpose of the standard is stated as 'encouraging building designers to assess and ensure successfully daylit spaces'. The standard document proposes verification methods for performing such assessments, albeit without recommending a simulation procedure for computing the aforementioned criteria. The workflows proposed in this paper are arguably the first attempt to standardize these assessment methods using de-facto open-source standard technologies currently used in practice. The approach of this work is twofold: establish that the compliance check can be systematically performed on a 3D model by a novel simulation tool developed by the authors; and highlighting the additional assumptions that need to be implemented to build a robust and unambiguous tool within existing open-source frameworks. 1 KEY INNOVATIONS• Formulating procedures for computational assessment of EN 17037 criteria for sunlight exposure and view out • Standardizing inputs and outputs for the proposed computational assessment procedures • Devising Python workflows utilizing the Radiance simulation engine and Honeybee from Ladybug Tools for running sunlight exposure and view analyses PRACTICAL IMPLICATIONSThe tool presented in this paper offers an open-source solution to check compliance with EN 17037 criteria for "View out" and "Exposure to sunlight". The tool will be made available to designers, consultants and researchers. Furthermore, the paper presents suggestions to policy-makers on how the compliance procedures could be made more robust and better integrated into computational design workflows.