| id |
cdrf2021_179 |
| authors |
Mirjam Konrad, Dana Saez, and Martin Trautz |
| year |
2021 |
| title |
Integration of Algorithm-Based Optimization into the Design Process of Industrial Buildings: A Case Study |
| source |
Proceedings of the 2021 DigitalFUTURES
The 3rd International Conference on Computational Design and Robotic Fabrication (CDRF 2021) |
| doi |
https://doi.org/https://doi.org/10.1007/978-981-16-5983-6_17
|
| summary |
Algorithm-based optimization is widely applied in many fields like industrial production, resulting in state-of-the-art workflows in the production process optimization. This project takes the cultural lag of conventional industrial architecture design as a motivation to investigate the implementation of algorithmbased optimization into traditional design processes. We argue that an enhanced way of architectural decision-making is possible. Current approaches use a translation of the whole design problem into a single, overly complicated optimization system. Contrary to that, this paper presents a novel workflow that defines precise design steps and applies optimizations only if suitable. Furthermore, this method can generate relevant results for factory planning design problems with contradicting factors, making it a promising approach for the complex challenges of i.e. resource-efficient building. |
| series |
cdrf |
| email |
mirjam.konrad@rwth-aachen.de |
| full text |
 file.pdf (3,259,918 bytes) |
| references |
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