Generative design in BIM for the automation of architectural solutions based on customer requirements

Introduction. The digital transformation of the architectural and construction industry has led to the active development of computer-aided design technologies, with generative design integrated into BIM modelling playing a special role. This research aims to analyze the current state and prospects of generative design application for architectural solutions automation considering diverse client requirements. The relevance of this work is due to the need to reduce design time while simultaneously improving quality and individuality of design solutions.

Materials and methods. The study is based on a systematic analysis of scientific publications from 2017–2023 on generative design and BIM technologies. A comparative study of existing software solutions (Autodesk Revit with Dynamo, Grasshopper for Rhino, IDEA StatiCa, Generative Components) was conducted. Expert evaluation methods were applied to determine the effectiveness of implementing generative algorithms, and the case study method was used to analyze implemented projects.

Results. Four dominant approaches to integrating generative design into BIM processes were identified: graph-based parametric modelling, evolutionary optimization, machine learning, and agent-based modelling. It was established that generative design algorithms can reduce design time by 35–40 % while simultaneously considering 5–7 times more design variants. A methodology for implementing generative algorithms was developed, covering the full cycle from formalizing client requirements to evaluating results. Key obstacles to widespread implementation were identified: insufficient standardization of technologies, complexity in formalizing subjective aesthetic criteria, and significant computational requirements for complex projects.

Conclusions. Generative design combined with BIM technologies is an effective tool for automating architectural design, allowing optimal solutions for complex multi-criteria problems. The proposed methodology systematizes the process of implementing generative algorithms into existing BIM workflows. Further technology development requires creating specialized libraries of typical generative components and methods for interpreting fuzzy client requirements.

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