| id |
ecaade2014_046 |
| authors |
Yazg_ Aksoy and Gülen Cagdas |
| year |
2014 |
| title |
A Model for Sustainable Site Layout Design with Pareto Genetic Algorithm: SSPM |
| doi |
https://doi.org/10.52842/conf.ecaade.2014.1.227
|
| source |
Thompson, Emine Mine (ed.), Fusion - Proceedings of the 32nd eCAADe Conference - Volume 1, Department of Architecture and Built Environment, Faculty of Engineering and Environment, Newcastle upon Tyne, England, UK, 10-12 September 2014, pp. 227-238 |
| wos |
WOS:000361384700022 |
| summary |
In architectural design, computer aided design tools have an important impact on design process, but still early design stage and sustainable design are problematic issues. During sustainable architectural design process, the designer needs to comply with some regulations, which requires calculations and comparisons. Green building certification systems are developed to assist designers during this complicated process, but for an efficient sustainable design for different regions, environmental information and local building codes must be considered with green building certification system criteria. In this paper, LEED and BREEAM certification systems are going to be considered as being the most representative building environment assessment schemes that are in use. As there are conflicting criteria's according to LEED and BREAM sustainable site parameters, local building codes and environmental conditions; an efficient decision support system can be developed by using multi-objective genetic algorithm. This paper presents an effective site-use multi-objective optimization model that use pareto genetic algorithm to determine the most efficient sustainable site layout design for social housing, which could assist designers in the early stage of design process. |
| keywords |
Sustainable site layout design; multi objective genetic algorithm; leed-breeam |
| series |
eCAADe |
| email |
|
| full text |
 file.pdf (361,207 bytes) |
| references |
Content-type: text/plain
|
Bentley, PJ (1999)
 Aspects of Evolutionary Design by Computer
, Roy, R, Furuhashi, T and Chawdrhy, PK (eds), Advances in Soft Computing, Springer, London, pp. 99-118
|
|
|
|
|
Deb, K (2001)
Multi-objective Optimization Using Evolutionary Algorithms
, John Wiley & Sons
|
|
|
|
|
Goldberg, DE (1989)
Genetic Algorithms in Search, Optimization and Machine Learning
, Addison-Wesley
|
|
|
|
|
Harputlugil, GU (2010)
Analysis and Simulation on Energy Performance Based Design
, Journal of Megaron, 6(1), pp. 1-12
|
|
|
|
|
Horn, J, Nafpliotis, N and Goldberg, DE (1994)
A Niched Pareto Genetic Algorithm for Multiobjective Optimization
, Proceedings of the First IEEE, pp. 82-87
|
|
|
|
|
Mitchell, M (1996)
An introduction to genetic algorithms
, The MIT Press
|
|
|
|
|
Rivard, H (2006)
Computer Assistance for Sustainable Building Design
, Smith, IFC (eds), Intelligent Computing in Engineering and Architecture, Springer-Verlag, Berlin, pp. 559-575
|
|
|
|
|
Wang, W, Zmeureanu, R and Rivard, H (2005)
Applying Multi-objective Genetic Algorithms in Green Building Design Optimization
, Building and Environment, 40(11), p. 1512–1525
|
|
|
|
|
Zelinska, AL, Church, R and Jankowski, P (2008)
Sustainable Urban Land Use Allocation with Spatial Optimization
, Geographical Information Science, 22(6), pp. 601-622
|
|
|
|
| last changed |
2022/06/07 07:57 |
|
