Möbius evolver: Competitive exploration of urban massing strategies

Patrick Janssen, Tung Do Phuong Bui, Likai Wang

Research output: Chapter in Book or Report/Conference proceedingChapterpeer-review

7 Citations (Scopus)

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 languageEnglish
Title of host publicationArtificial Intelligence in Urban Planning and Design
Subtitle of host publicationTechnologies, Implementation, and Impacts
PublisherElsevier
Pages293-321
Number of pages29
ISBN (Electronic)9780128239414
ISBN (Print)9780128239421
DOIs
Publication statusPublished - 1 Jan 2022

Keywords

  • Competitive evolutionary design
  • Design exploration
  • Evolutionary optimization
  • Evolutionary programming
  • Urban massing

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