Generative design is an iterative design process that involves a program that will generate a certain number of outputs that meet certain constraints, and a designer that will fine tune the feasible region by changing minimal and maximal values of an interval in which a variable of the program meets the set of constraints, in order to reduce or augment the number of outputs to choose from. The program doesn't need to be run on a machine like a digital computer, it can be run by a human for example with pen and paper. The designer doesn't need to be a human, it can be a test program in a testing environment or an artificial intelligence (see for example Generative adversarial networks). The designer learns to refine the program with each iteration as his design goals become better defined over time.
The output could be images, sounds, architectural models, animation and many 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.
The process combined with the power of digital computers that can explore a very large number of possible permutations of a solution enables designers to generate brand new options, beyond what a human alone could create, to arrive at a most effective and optimized design. It mimics nature’s evolutionary approach to design through genetic variation and selection.
Generative design is becoming 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. It is also facilitated with tools in commercially available CAD packages.
- Generative art
- Computer art
- System dynamics
- Genetic algorithms
- Random number generation
- Procedural modeling
- Topology optimization
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