A performance comparison of multi-objective optimization algorithms for solving nearly-zero-energy-building design problems

•Integrated building design is inherently a multi-objective optimization problem.•Recently, many multi-objective optimization algorithms have been developed.•The performance of seven multi-objective evolutionary are tested in solving a nZEB design case.•The performance of studied algorithms is ranke...

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Veröffentlicht in:	Energy and buildings Jg. 121; S. 57 - 71
Hauptverfasser:	Hamdy, Mohamed, Nguyen, Anh-Tuan, Hensen, Jan L.M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 01.06.2016
Schlagworte:	Algorithms Building simulation Comparison Design of buildings Evolutionary algorithms Experimentation Genetic algorithms Mathematical models Multi-objective optimization Odonata Optimization Running Sorting DMn ENSES Building simulation pNSGA-II EPBD MOOA evMOGA DHW HVAC Comparison Experimentation GA MOEA NoPsolution BOP spMODE-II e MOPSO IGDn LCC PSO PEC FIT GDn Algorithms PR_GA nZEB Multi-objective optimization MODA NSGA
ISSN:	0378-7788
Online-Zugang:	Volltext
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