Generative workplace and space planning in architectural practice. (September 2022)

• Record Type: Journal Article
• Authors: Okhoya, Victor W; Bernal, Marcelo; Economou, Athanassios; Saha, Nirvik; Vaivodiss, Robert; Hong, Tzu-Chieh K; Haymaker, John
• Other Names: Gómez Paula Z guest-editor.; Braida Frederico guest-editor.; Lima Fernando guest-editor.; Loyola Mauricio guest-editor.
• Is Part Of: International journal of architectural computing. Volume 20:Number 3(2022)
• Page Start: 645
• Page End: 672
• Publication Date: 2022-09
• Subjects: Generative design -- shape grammar -- space allocation -- space planning; Architecture -- Data processing -- Periodicals; Architecture -- Informatique -- Périodiques; Virtual reality in architecture -- Periodicals; Computer-aided design -- Periodicals; Architecture -- Data processing; Periodicals; 720.2840285536
• DOI: 10.1177/14780771221120580
• Languages: English
• ISSNs: 1478-0771

Abstract

Generative design is emerging as an important approach for design exploration and design analysis in architectural practice. At the interior design scale, although many approaches exist, they do not meet many requirements for implementing generative design in practice. These requirements include the need for end-user accessible tools and skills, rapid execution, the use of standard inputs and outputs, and being scalable and reusable. In this paper, we describe a hybrid process that uses both space allocation and shape grammar algorithms to solve workplace and space planning interior design problems. Space allocation algorithms partition spaces according to program requirements while shape grammar automates the placement of inventory and the production of high-resolution drawings. We evaluate using three real world example projects how this hybrid approach meets the identified requirements of generative space planning in architectural practice.