2018
DOI: 10.1017/s0890060418000033
|View full text |Cite
|
Sign up to set email alerts
|

Quantifying diversity in parametric design: a comparison of possible metrics

Abstract: To be useful for architects and related designers searching for creative, expressive forms, performance-based digital tools must generate a diverse range of design solutions. This gives the designer flexibility to choose from a number of high-performing designs based on aesthetic preferences or other priorities. However, there is no single established method for measuring diversity in the context of computational design, especially in the field of architecture. This paper explores different metrics for quantif… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
5
0

Year Published

2020
2020
2023
2023

Publication Types

Select...
4
2
1

Relationship

2
5

Authors

Journals

citations
Cited by 12 publications
(5 citation statements)
references
References 53 publications
0
5
0
Order By: Relevance
“…Moreover, providing applicable optimization methods for target problems within the space requires an accurate description of the solution space based on systematic knowledge of BIM models' underlying constraints and dependencies. For instance, as the design goes on, similarity analysis based on the priority of building design parameters (Brown and Mueller 2019) becomes necessary to quantify and qualify the variation between various solutions among the whole design set. The raw "distance" between those designs indicates the similarity and the difference between variants (Anandan et al 2006).…”
Section: Solution Space Formationmentioning
confidence: 99%
“…Moreover, providing applicable optimization methods for target problems within the space requires an accurate description of the solution space based on systematic knowledge of BIM models' underlying constraints and dependencies. For instance, as the design goes on, similarity analysis based on the priority of building design parameters (Brown and Mueller 2019) becomes necessary to quantify and qualify the variation between various solutions among the whole design set. The raw "distance" between those designs indicates the similarity and the difference between variants (Anandan et al 2006).…”
Section: Solution Space Formationmentioning
confidence: 99%
“…During the option evaluation phase of design, complexity can be interpreted as diversity. Brown and Mueller [9] investigated multiple metrics of diversity in the context of parametric design exploration. The values of each design-changing parameter are represented as components of a point in R n , with different points in the parameter space representing different designs.…”
Section: Design Complexity and Rationalizationmentioning
confidence: 99%
“…In [9], a quantifiable measure of design variation was presented. However, the method quantifies inter-design variation, rather than variation within a single design, and does not consider internal force magnitudes.…”
Section: Research Gap and Contributionsmentioning
confidence: 99%
“…During the option evaluation phase of design, complexity can be interpreted as diversity. Brown and Mueller (2019) investigated multiple metrics of diversity in the context of parametric design exploration. The values of each design-changing parameter are represented as components of a point in R n , with different points in the parameter space representing different designs.…”
Section: Design Complexity and Rationalizationmentioning
confidence: 99%
“…In Brown and Mueller (2019), a quantifiable measure of design variation was presented. However, the method quantifies inter-design variation, rather than variation within a single design, and does not consider internal force magnitudes.…”
Section: Research Gap and Contributionsmentioning
confidence: 99%