Abstract
During the early stages of design exploration, competing design strategies are typically considered. This chapter presents a design method, supported by a novel type of evolutionary algorithm, that maintains a heterogeneous population of design variants based on competing design strategies. Each strategy defines its own search space of design variants, all sharing a common generative concept or idea. A population of design variants is evolved through a process of selection and variation. As evolution progresses, some design strategies will become extinct while others will gradually dominate the population. A demonstration is presented showing how a designer can explore competing strategies by running a series of iterative evolutionary searches. The evolutionary algorithm has been implemented on a cloud platform, thereby allowing populations design variants to be processed in parallel. This results in a significant reduction in computation time, allowing thousands of designs to be evolved in just a few minutes.
| Original language | English |
|---|---|
| Title of host publication | Artificial Intelligence in Urban Planning and Design |
| Subtitle of host publication | Technologies, Implementation, and Impacts |
| Publisher | Elsevier |
| Pages | 293-321 |
| Number of pages | 29 |
| ISBN (Electronic) | 9780128239414 |
| ISBN (Print) | 9780128239421 |
| DOIs | |
| Publication status | Published - 1 Jan 2022 |
Keywords
- Competitive evolutionary design
- Design exploration
- Evolutionary optimization
- Evolutionary programming
- Urban massing
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