Citation: Gradišar, L.; Klinc, R.; Turk,
Ž.; Dolenc, M. Generative Design
Methodology and Framework
Exploiting Designer-Algorithm
Synergies. Buildings 2022, 12, 2194.
https://doi.org/10.3390/
buildings12122194
Academic Editors: Yuan Chen,
Xianfei Yin, Bo Xiao, Yinghua Shen
and Hexu Liu
Received: 19 October 2022
Accepted: 8 December 2022
Published: 12 December 2022
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buildings
Article
Generative Design Methodology and Framework Exploiting
Designer-Algorithm Synergies
Luka Gradišar * , Robert Klinc , Žiga Turk and Matevž Dolenc
Faculty of Civil and Geodetic Engineering, University of Ljubljana, Jamova 2, 1000 Ljubljana, Slovenia
* Correspondence: luka.gradisar@fgg.uni-lj.si
Abstract: Designing is a problem-solving activity. The process is usually iterative: a solution is
proposed, then analysed and tested until it satisfies all constraints and best fulfils the criteria. Usually,
a designer proposes a solution based on intuition, experience, and knowledge. However, this does
not work for problems they are facing for the first time. An alternative approach is generative
design, where the designer focuses on iteratively defining a problem with its constraints and criteria
in the form of a parametric computational model, and then leaves the search for the solution to
the algorithms and their ability to rapidly generate and test several alternatives. The result of this
approach is not only a set of solutions embedding implicitly the knowledge but also a model where
problem-defining knowledge is quite explicit. The idea of the proposed approach is the exploitation
of synergies between the designer and the algorithms. The designer focuses on problem definition
and the algorithm focuses on finding a solution, showing that the capacity of the generative approach
to replace the designer is limited. In the paper, we first present the framework of generative design,
then apply the process to a case study of designing an efficient shading solution, and in the end,
we present the results and compare them with the traditional approach. The approach is general
and can be applied in other areas of engineering. It is relevant both to designers as well as software
developers who are expected to take this approach further. More theoretical work is needed to study
problem definitions as a form of knowledge representation in engineering.
Keywords: generative design; optimisation; computational design; parametric modelling; BIM;
automation; shading study
1. Introduction
In recent years, technological development has accelerated drastically. This is re-
flected in the increasing use of digital tools being introduced in the construction industry.
The work of designers over time has already changed by replacing pen and paper with
computer-aided design (CAD) tools and now with Building Information Modelling (BIM).
Building design is becoming more comprehensive, interconnected, and coordinated, but
it still involves a lot of manual work and especially rework. Traditionally, the designer
proposes the solution based on their experience, previous projects, and creativity under
the given conditions and objectives, while the computers are to help with presentation,
documentation, and analysis, but other alternatives may be considered to assist in design
development.
One such approach is generative design, where the main idea is the collaboration
between the designer and the computer/algorithm, which has complementary capabilities,
such as, on the one hand, sorting large amounts of data, generating and analysing a large
number of results, finding optimal solutions, and iterative improvement of the solution [1,2];
on the other hand, real world experience, deep knowledge, understanding, and history of
working in the field. In this process, we shift the focus from creating the design solution to
defining the design problem with its constraints and criteria, where a well-defined problem
Buildings 2022, 12, 2194. https://doi.org/10.3390/buildings12122194 https://www.mdpi.com/journal/buildings