Advances in Computational Design

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Optimization of settlement layout based on parametric generation

  • Song, Jinghua (School of Urban Design, Wuhan University) ;
  • Xie, Xinqin (School of Urban Design, Wuhan University) ;
  • Yu, Yang (School of Urban Design, Wuhan University)
  • Received : 2017.11.17
  • Accepted : 2018.01.19
  • Published : 2018.01.25
⟨ Previous Next ⟩

Abstract

Design of settlement space is a complicated process while reasonable spatial layout bears great significance on the development and resource allocation of a settlement. The study proposes a weighted L-system generation algorithm based on CA (Cellular Automation) model which tags the spatial attributes of cells through changes in their state during the evolution of CA and thus identifies the spatial growth mode of a settlement. The entrance area of the Caidian Botanical and Animal Garden is used a case study for the model. A design method is proposed which starts from the internal logics of spatial generation, explores possibility of spatial rules and realizes the quantitative analysis and dynamic control of the design process. Taking a top-down approach, the design method takes into account the site information, studies the spatial generation mechanism of settlements and further presents a engine for the generation of multiple layout proposals based on different rules. A optimal solution is acquired using GA (Genetic Algorithm) which generates a settlement spatial layout carrying site information and dynamically linked to the surround environment. The study aims to propose a design method to optimize the spatial layout of the complex settlement system based on parametric generation.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation

References

  1. Celestino, S. (2015), Generative Design Futuring Past.
  2. Charles Jencks (2007), Critical Modernism: Where is Post-Modernism Going What is Post-Modernism, Academy Press.
  3. Leng, T. (2011), Digital architectural design guide by complexity theory, South China University of Technology, 140-142.
  4. Li, X. (2009), Research and application of particle swarm optimization based on simulated annealing method in the urban layout of the land space, Shandong Normal University, 11-13.
  5. Li, X. and Xu, W. (2015), "The application of algorithm and digital modeling techniques in architectural design", New Architecture, (5), 10-14.
  6. Lin, Q. (2013), "Architectural fractal generating based on 3D IFS methodology", World Architecture, (9), 106-109.
  7. Lin, Q. (2015), "Particle system and fractal movement", Urbanism and Architecture, 1-3.
  8. Luo, Y. (2015), Optimization research of the parametric architecture based on optimizing method, Southwest Jiaotong University, 55-68.
  9. Neil, L. (2009), "Swarm Urbanism", World Architecture, 1-2.
  10. Shen, J. (2012), Research on methods of using technical analysis in grasshopper for green building design, South China University of Technology, 41-49.
  11. Song, J., Zhao, B., Xiong, Y. and Guo, X. (2009), "Quantitative analysis of contributing factors in settlement generation", J. Civil. Architect. Environ. Eng., 31(2), 110-115.
  12. Xu, W. (2012), "Parametric design and generating by algorithm", Urban Environ. Des., (1), 250-253.
  13. Yu, H. (2011), Parametric Urban Design Based on Rhinoceros: A Case Study of Jixian Urban Center.