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Algorithms for optimization of building design: A review

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  • Machairas, Vasileios
  • Tsangrassoulis, Aris
  • Axarli, Kleo

Abstract

Building design is quite a complicated task with the design team trying to counterbalance various antagonistic parameters, which in turn are subject to various constraints. Due to this complexity, performance simulation tools are employed and as a consequence, optimization methods have just started being used, mainly as a decision aid. There are examples, amongst the architectural community, where probabilistic evolutionary algorithms or other derivative-free methods have been used with various decision variables and objective goals. This paper is a review of the methods and tools used for the building design optimization in an effort to explore the reasoning behind their selection, to present their abilities and performance issues and to identify the key characteristics of their future versions.

Suggested Citation

  • Machairas, Vasileios & Tsangrassoulis, Aris & Axarli, Kleo, 2014. "Algorithms for optimization of building design: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 101-112.
    • Handle: RePEc:eee:rensus:v:31:y:2014:i:c:p:101-112
    DOI: 10.1016/j.rser.2013.11.036
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    References listed on IDEAS

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    1. Mechri, Houcem Eddine & Capozzoli, Alfonso & Corrado, Vincenzo, 2010. "USE of the ANOVA approach for sensitive building energy design," Applied Energy, Elsevier, vol. 87(10), pages 3073-3083, October.
    2. Chantrelle, Fanny Pernodet & Lahmidi, Hicham & Keilholz, Werner & Mankibi, Mohamed El & Michel, Pierre, 2011. "Development of a multicriteria tool for optimizing the renovation of buildings," Applied Energy, Elsevier, vol. 88(4), pages 1386-1394, April.
    3. Cumming, Douglas & Helge Haß, Lars & Schweizer, Denis, 2013. "Private equity benchmarks and portfolio optimization," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3515-3528.
    4. Rakha, Tarek & Nassar, Khaled, 2011. "Genetic algorithms for ceiling form optimization in response to daylight levels," Renewable Energy, Elsevier, vol. 36(9), pages 2348-2356.
    5. Heiselberg, Per & Brohus, Henrik & Hesselholt, Allan & Rasmussen, Henrik & Seinre, Erkki & Thomas, Sara, 2009. "Application of sensitivity analysis in design of sustainable buildings," Renewable Energy, Elsevier, vol. 34(9), pages 2030-2036.
    6. Petersen, Steffen & Svendsen, Svend, 2012. "Method for component-based economical optimisation for use in design of new low-energy buildings," Renewable Energy, Elsevier, vol. 38(1), pages 173-180.
    7. Wong, S.L. & Wan, Kevin K.W. & Lam, Tony N.T., 2010. "Artificial neural networks for energy analysis of office buildings with daylighting," Applied Energy, Elsevier, vol. 87(2), pages 551-557, February.
    8. Shi, Xing, 2011. "Design optimization of insulation usage and space conditioning load using energy simulation and genetic algorithm," Energy, Elsevier, vol. 36(3), pages 1659-1667.
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