Generative design

Generative design is an iterative design process that uses software to generate outputs that fulfill a set of constraints iteratively adjusted by a designer. Whether a human, test program, or artificial intelligence, the designer algorithmically or manually refines the feasible region of the program's inputs and outputs with each iteration to fulfill evolving design requirements.^[1] By employing computing power to evaluate more design permutations than a human alone is capable of, the process is capable of producing an optimal design that mimics nature's evolutionary approach to design through genetic variation and selection.^{[citation needed]} The output can be images, sounds, architectural models, animation, and much more. It is therefore a fast method of exploring design possibilities that is used in various design fields such as art, architecture, communication design, and product design.^[2]

Generative design has become more important, largely due to new programming environments or scripting capabilities that have made it relatively easy, even for designers with little programming experience, to implement their ideas.^[3] Additionally, this process can create solutions to substantially complex problems that would otherwise be resource-exhaustive with an alternative approach making it a more attractive option for problems with a large or unknown solution set.^[4] It is also facilitated with tools in commercially available CAD packages.^[5] Not only are implementation tools more accessible, but also tools leveraging generative design as a foundation.^[6]

^ Meintjes, Keith. ""Generative Design" – What's That? - CIMdata". Retrieved 2018-06-15.
^ ENGINEERING.com. "Generative Design: The Road to Production". www.engineering.com. Retrieved 2019-12-05.
^ Schwab, Katharine (16 April 2019). "This is the first commercial chair made using generative design". Fast Company. Retrieved 13 August 2019.
^ Prasanta, Rajamoney, Shankar A. Rosenbloom, Paul S.; Wagner, Chris Bose (2014-09-04). Compositional model-based design: A generative approach to the conceptual design of physical systems. University of Southern California. OCLC 1003551283.{{cite book}}: CS1 maint: multiple names: authors list (link)
^ Barbieri, Loris; Muzzupappa, Maurizio (2022). "Performance-Driven Engineering Design Approaches Based on Generative Design and Topology Optimization Tools: A Comparative Study". Applied Sciences. 12 (4): 2106. doi:10.3390/app12042106.
^ Anderson, Fraser; Grossman, Tovi; Fitzmaurice, George (2017-10-20). Trigger-Action-Circuits: Leveraging Generative Design to Enable Novices to Design and Build Circuitry. ACM. pp. 331–342. doi:10.1145/3126594.3126637. ISBN 9781450349819. S2CID 10091635.

[1] Meintjes, Keith. ""Generative Design" – What's That? - CIMdata". Retrieved 2018-06-15.

[2] ENGINEERING.com. "Generative Design: The Road to Production". www.engineering.com. Retrieved 2019-12-05.

[3] Schwab, Katharine (16 April 2019). "This is the first commercial chair made using generative design". Fast Company. Retrieved 13 August 2019.

[4] Prasanta, Rajamoney, Shankar A. Rosenbloom, Paul S.; Wagner, Chris Bose (2014-09-04). Compositional model-based design: A generative approach to the conceptual design of physical systems. University of Southern California. OCLC 1003551283.{{cite book}}: CS1 maint: multiple names: authors list (link)

[5] Barbieri, Loris; Muzzupappa, Maurizio (2022). "Performance-Driven Engineering Design Approaches Based on Generative Design and Topology Optimization Tools: A Comparative Study". Applied Sciences. 12 (4): 2106. doi:10.3390/app12042106.

[6] Anderson, Fraser; Grossman, Tovi; Fitzmaurice, George (2017-10-20). Trigger-Action-Circuits: Leveraging Generative Design to Enable Novices to Design and Build Circuitry. ACM. pp. 331–342. doi:10.1145/3126594.3126637. ISBN 9781450349819. S2CID 10091635.

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