In the light of the regulations on buildings energy performance, the designers face the need to choose among alternative design solutions, having to assess their effectiveness according to several -sometimes conflicting- points of view, such as the energy saving, the indoor comfort, the environmental and economic impact. This paper reports the results of the application of genetic algorithms to solve this “multi-objective optimization problem” in a building retrofit intervention in Italy. The results, even if related to a single case-study, suggest the optimal efficiency measures, whose robustness was tested in different Italian climatic zones.

Existing buildings retrofit through multi-objective optimization: a case-study / Di Giuseppe, E; Galdenzi, G; D'Orazio, M; Di Perna, C. - In: TEMA. - ISSN 2421-4574. - 4:2(2018), pp. 1-12. [10.17410/tema.v4i2.189]

Existing buildings retrofit through multi-objective optimization: a case-study

Di Giuseppe, E
;
D'Orazio, M;Di Perna, C
2018-01-01

Abstract

In the light of the regulations on buildings energy performance, the designers face the need to choose among alternative design solutions, having to assess their effectiveness according to several -sometimes conflicting- points of view, such as the energy saving, the indoor comfort, the environmental and economic impact. This paper reports the results of the application of genetic algorithms to solve this “multi-objective optimization problem” in a building retrofit intervention in Italy. The results, even if related to a single case-study, suggest the optimal efficiency measures, whose robustness was tested in different Italian climatic zones.
2018
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/262373
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