2020
DOI: 10.1680/jensu.19.00041
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A genetic algorithm-based envelope design optimisation for residential buildings

Abstract: National energy standards of countries worldwide require a wide range of measures to be used in energy policies. It has become a challenge to fulfil different measures of building envelope design optimisation through enhancement of energy conservation. To overcome this challenge, this study proposes an optimisation model for determining the optimum envelope design of a reference building in four climate regions. The optimisation model utilised a genetic algorithm, as an optimisation tool, and national standard… Show more

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Cited by 6 publications
(2 citation statements)
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“…Similar to other studies, the optimum envelope configuration has the smallest window area possible and the software selected high-efficiency windows with relatively higher cost [3,6,45]. In addition, the developed optimization software recommended insulation thicknesses similar to other studies that aimed to optimize reference buildings located in Turkey using commercial software [46,47,48,49]. The optimization software selected walls with a relatively lower cost and thicker insulations.…”
Section: Discussionmentioning
confidence: 93%
“…Similar to other studies, the optimum envelope configuration has the smallest window area possible and the software selected high-efficiency windows with relatively higher cost [3,6,45]. In addition, the developed optimization software recommended insulation thicknesses similar to other studies that aimed to optimize reference buildings located in Turkey using commercial software [46,47,48,49]. The optimization software selected walls with a relatively lower cost and thicker insulations.…”
Section: Discussionmentioning
confidence: 93%
“…Caglayan et al [4] analyzed the heating energy consumption and material cost for four different climate zones in Turkey, taking into account the window type, wall insulation, ceiling insulation, and basement floor insulation material thicknesses. They developed an optimization tool by using numerical calculation formulas in genetic algorithm (GA).…”
Section: Introductionmentioning
confidence: 99%