"The role of latent representations for design space exploration of flo" by Vahid Azizi, Muhammad Usman et al.
 

The role of latent representations for design space exploration of floorplans

Document Type

Article

Publication Date

11-1-2023

Abstract

Floorplans often require considering numerous factors, from the layout size to cost, numeric attributes such as room sizes, and other intrinsic properties such as connectivity between visible regions. Representing these complex factors is challenging, but doing so in a representative and efficient way can enable new modes of design exploration. Existing image and graph-based approaches of floorplans’ representation often failed to consider low-level space semantics, structural features, and space utilization with respect to its future inhabitants, which are all the critical elements to analyze design layouts. We present a latent-space representation of floorplans using gated recurrent unit variational autoencoder (GRU-VAE), where floorplans are represented as attributed graphs (encoded with the abovementioned features). Two local search approaches are presented to efficiently explore the latent space for optimizing and generating new floorplans for the given environment. Semantic, structural, and visibility metrics are evaluated individually and as a combined objective for optimizations.

Identifier

85138407958 (Scopus)

Publication Title

Simulation

External Full Text Location

https://doi.org/10.1177/00375497221115734

e-ISSN

17413133

ISSN

00375497

First Page

1167

Last Page

1179

Issue

11

Volume

99

Grant

IIS-1703883

Fund Ref

National Science Foundation

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