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Understanding the Span of Design Spaces

And Its Implication for Performance-Based Design Optimization

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Computer-Aided Architectural Design. Design Imperatives: The Future is Now (CAAD Futures 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1465))

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Abstract

This paper presents a study investigating the impact of design spaces on performance-based design optimization and attempts to demonstrate the relationship between these two factors through the lens of the span of design spaces. The study defines the span of design spaces as the variety of different types of building design that can be embodied by the parametric model; thus, the wider the span, the more likely is the optimization to identify promising types of building design. In order to reveal the relationship between the span of design spaces and performance-based design optimization, the study present a case study that includes design spaces with various spans within a building design optimization problem considering daylighting performance. The result shows that the difference in span can result in significant changes in optimization in relation to fitness and architectural implications.

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References

  1. Wang, L., Chen, K.W., Janssen, P., Ji, G.: Enabling optimisation-based exploration for building massing design: a coding-free evolutionary building massing design toolkit in rhino-grasshopper. In: RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference, pp. 255–264 (2020)

    Google Scholar 

  2. Wang, L., Janssen, P., Ji, G.: Reshaping design search spaces for efficient computational design optimization in architecture. In: Proceedings of the 10th International Conference on Computational Creativity, ICCC 2019 (2019)

    Google Scholar 

  3. Woodbury, R.F., Burrow, A.L.: Whither design space? AIE EDAM Artif. Intell. Eng. Des. Anal. Manuf. 20, 63–82 (2006). https://doi.org/10.10170S0890060406060057

  4. Wang, L., Janssen, P., Ji, G.: Efficiency versus effectiveness: a study on constraint handling for architectural evolutionary design. In: Learning, Prototyping and Adapting - Proceedings of the 23rd CAADRIA Conference, pp. 163–172 (2018)

    Google Scholar 

  5. Wang, L., Janssen, P., Ji, G.: Progressive modelling for parametric design optimization. In: Haeusler, M.A., Schnabel, T.F. (eds.) Intelligent and Informed - Proceedings of the 24th CAADRIA Conference, pp. 383–392 (2019)

    Google Scholar 

  6. Wang, L., Janssen, P., Ji, G.: Utility of evolutionary design in architectural form finding: an investigation into constraint handling strategies. In: Gero, J.S. (ed.) DCC 2018, pp. 177–194. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-05363-5_10

    Chapter  Google Scholar 

  7. Akin, Ö.: Variants in design cognition. In: Design Knowing & Learning Cognition in Design Education, pp. 105–124. Elsevier (2001)

    Google Scholar 

  8. Sheikholeslami, M.: Design space exploration. In: Woodbury, R. (ed.) Elements of Parametric Design, pp. 275–287. Routledge, Abingdon (2010)

    Google Scholar 

  9. Wang, L., Janssen, P., Chen, K.W., Tong, Z., Ji, G.: Subtractive building massing for performance-based architectural design exploration: a case study of daylighting optimization. Sustain. 11, 6965 (2019). https://doi.org/10.3390/su11246965

    Article  Google Scholar 

  10. Wang, L., Chen, K.W., Janssen, P., Ji, G.: Algorithmic generation of architectural massing models for building design optimisation: parametric modelling using subtractive and additive form generation principles. In: RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th CAADRIA Conference, pp. 385–394 (2020)

    Google Scholar 

  11. Wang, L., Janssen, P., Ji, G.: SSIEA: a hybrid evolutionary algorithm for supporting conceptual architectural design. Artif. Intell. Eng. Des. Anal. Manuf. 34, 458–476 (2020). https://doi.org/10.1017/S0890060420000281

    Article  Google Scholar 

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Correspondence to Likai Wang .

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Wang, L. (2022). Understanding the Span of Design Spaces. In: Gerber, D., Pantazis, E., Bogosian, B., Nahmad, A., Miltiadis, C. (eds) Computer-Aided Architectural Design. Design Imperatives: The Future is Now. CAAD Futures 2021. Communications in Computer and Information Science, vol 1465. Springer, Singapore. https://doi.org/10.1007/978-981-19-1280-1_18

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  • DOI: https://doi.org/10.1007/978-981-19-1280-1_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-19-1279-5

  • Online ISBN: 978-981-19-1280-1

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