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A Model for Sustainable Site Layout Design of Social Housing with Pareto Genetic Algorithm: SSPM

Part of the Communications in Computer and Information Science book series (CCIS,volume 527)

Abstract

Nowadays as the aim to reduce the environmental impact of buildings becomes more apparent, a new architectural design approach is gaining momentum called sustainable architectural design. Sustainable architectural design process includes some regulations itself, which requires calculations, comparisons and consists of several possible conflicting objectives that need to be considered together. A successful green building design can be performed by the creation of alternative designs generated according to all the sustainability parameters and local regulations in conceptual design stage. As there are conflicting criteria’s according to LEED and BREAM sustainable site parameters, local regulations and local climate conditions, an efficient decision support system can be developed by the help of Pareto based non-dominated genetic algorithm (NSGA-II) which is used for several possibly conflicting objectives that need to be considered together. In this paper, a model which aims to produce site layout alternatives according to sustainability criteria for cooperative apartment house complexes, will be mentioned.

Keywords

  • Sustainable site layout design
  • Multi objective genetic algorithm
  • LEED-BREEAM

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References

  1. Bentley, P.J.: Aspects of evolutionary design by computers. In: Roy, R., Furuhashi, T., Chawdhry, P.K. (eds.) Advances in Soft Computing, pp. 99–118. Springer, London (1999). Department of Computer Science, University College, London

    CrossRef  Google Scholar 

  2. Rivard, H.: Computer assistance for sustainable building design. In: Smith, I.F.C. (ed.) Intelligent Computing in Engineering and Architecture, EG-ICE 2006, pp. 559–575. Springer, Berlin (2006)

    CrossRef  Google Scholar 

  3. Cole, R.J., Larsson, N.: GBTool user manual, Green Building Challenge (2002)

    Google Scholar 

  4. Trusty, W.B., Meil, J.K.: Introducing ATHENA™ v. 2.0: an LCA based decision support tool for assessing the environmental impact of the built environment. In: Proceedings of the eSim 2002, the Canadian Conference on Building Energy Simulation, Montréal, Canada (2002)

    Google Scholar 

  5. Wang, W., Zmeureanu, R., Rivard, H.: Applying multi objective genetic algorithms in green building design optimization. Build. Environ. 40(11), 1512–1525 (2005). Elsevier

    CrossRef  Google Scholar 

  6. Radford, A.D., Gero, J.S.: Design by Optimization in Architecture, Building and Construction. Van Nostrand Reinhold, New York (1987)

    Google Scholar 

  7. Harputlugil, G.U.: Analysis and simulation on energy performance based design. J. Megaron 6(1), 1–12 (2010)

    Google Scholar 

  8. Mitchell, M.: An introduction to genetic algorithms. A Bradford Book, The MIT Press, Cambridge, Massachusetts, pp. 7–12 (1996)

    Google Scholar 

  9. Goldberg, D.E.: Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading (1989)

    MATH  Google Scholar 

  10. Deb, K.: Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester (2001)

    MATH  Google Scholar 

  11. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)

    CrossRef  Google Scholar 

  12. Lahanas, M., Baltas, D., Zamboglou, N.: A hybrid evolutionary algorithm for multiobjective anatomy based dose optimization in HDR brachytherapy. Phys. Med. Biol. 48(3), 399–415 (2003)

    CrossRef  Google Scholar 

  13. Zelinska, A.L., Church, R., Jankowski, P.: Sustainable urban land use allocation with spatial optimization. J. Geog. Inf. Sci. 22(6), 601–622 (2008)

    CrossRef  Google Scholar 

  14. USGBC: LEED for new construction & major renovations, v. 2.2, USA (2005)

    Google Scholar 

  15. BREEAM: BRE Environmental Assessment Method, UK (2008)

    Google Scholar 

  16. Istanbul Zoning Regulations, Turkey (2007)

    Google Scholar 

  17. TS825: Rules of thermal insulation in buildings, Turkish Standards Institute, Turkey (1999)

    Google Scholar 

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Correspondence to Yazgı Badem Aksoy .

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Aksoy, Y.B., Çağdaş, G., Balaban, Ö. (2015). A Model for Sustainable Site Layout Design of Social Housing with Pareto Genetic Algorithm: SSPM. In: Celani, G., Sperling, D., Franco, J. (eds) Computer-Aided Architectural Design Futures. The Next City - New Technologies and the Future of the Built Environment. CAAD Futures 2015. Communications in Computer and Information Science, vol 527. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-47386-3_7

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  • DOI: https://doi.org/10.1007/978-3-662-47386-3_7

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