| id |
ijac202321411 |
| authors |
Khodadadi, Anahita |
| year |
2023 |
| title |
A Generative Design Exploration Methodology for Integration of Structural, Environmental, and User Agencies in an Early Design Stage |
| source |
International Journal of Architectural Computing 2023, Vol. 21 - no. 4, 757-780 |
| summary |
This article presents a generative design exploration methodology utilized to assist designers in problem structuring and decision-making in a multi-disciplinary setting. This novel design exploration methodology is based on the hybridization of a genetic algorithm (GA) and the Theory of Innovative Problem Solving (TRIZ). This methodology allows investigation of unexpected solutions, application of innovative ideas for resolving contradictory design objectives, and continuous interaction between designers and the search engine. In this study, the design case of a mid-rise apartment complex is used to examine the capacity of the proposed multi-agent design exploration method. Accordingly, both quality and numeric performance-based values of the design alternatives, including the visual appearance of the complex and apartments’ shadows over one another, structural and energy efficiency, and life-cycle impact of the building’s structural system, are investigated to demonstrate the usability and benefits of the developed method. |
| keywords |
Conceptual design, design exploration, TRIZ, genetic algorithm, multi-objective design, Cross-Laminated Timber (CLT) plates, informed decision-making, life-cycle assessment |
| series |
journal |
| references |
Content-type: text/plain
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| last changed |
2024/04/17 14:30 |
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