Applying multi-objective genetic algorithms in green building design optimization

Since buildings have considerable impacts on the environment, it has become necessary to pay more attention to environmental performance in building design. However, it is a difficult task to find better design alternatives satisfying several conflicting criteria, especially, economical and environm...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:Building and environment Ročník 40; číslo 11; s. 1512 - 1525
Hlavní autori: Wang, Weimin, Zmeureanu, Radu, Rivard, Hugues
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier Ltd 01.11.2005
Predmet:
Building design
Green building
Life cycle assessment
Life cycle cost
Multi-objective genetic algorithm
Life cycle assessment
Multi-objective genetic algorithm
Green building
Life cycle cost
Building design
ISSN:0360-1323, 1873-684X
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Since buildings have considerable impacts on the environment, it has become necessary to pay more attention to environmental performance in building design. However, it is a difficult task to find better design alternatives satisfying several conflicting criteria, especially, economical and environmental performance. This paper presents a multi-objective optimization model that could assist designers in green building design. Variables in the model include those parameters that are usually determined at the conceptual design stage and that have critical influence on building performance. Life cycle analysis methodology is employed to evaluate design alternatives for both economical and environmental criteria. Life cycle environmental impacts are evaluated in terms of expanded cumulative exergy consumption, which is the sum of exergy consumption due to resource inputs and abatement exergy required to recover the negative impacts due to waste emissions. A multi-objective genetic algorithm is employed to find optimal solutions. A case study is presented and the effectiveness of the approach is demonstrated for identifying a number of Pareto optimal solutions for green building design.
Bibliografia:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ObjectType-Article-1
ObjectType-Feature-2
ISSN:0360-1323
1873-684X
DOI:10.1016/j.buildenv.2004.11.017