Optimization of green building design to achieve green building index (GBI) using genetic algorithm (GA)

Harun, Muhamad Farhin; Samah, Azurah A.; Majid, Hairudin Abdul; Yusoff, Yusliza Mohd; Lim, Yaik Wah

doi:10.1109/ict-ispc.2017.8075310

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…Another envelope optimization initiative was recorded by in [8], where a genetic algorithm mono-objective was developed to optimize an environmentally friendly building projected by BIM technology, seeking to find a greater combination of construction material that produces an OTTV (General Thermal Transfer Value) and an envelope energy performance indicator closest to the ideal as possible. The initial result showed that the genetic algorithm could find an ideal combination of materials with a reduced OTTV of 16%.…”

Section: Envelopementioning

confidence: 99%

Methodology for Energy Efficiency on Lighting and Air Conditioning Systems in Buildings Using a Multi-Objective Optimization Algorithm

Monteiro

Tostes

et al. 2020

Energies

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The purpose of this article is to develop a methodology to apply to multi-objective optimization algorithms aimed at energy efficiency in buildings, considering aspects such as incremental cost, energy consumption, greenhouse gas emissions and energy efficiency levels of lighting and air conditioning system, according to the mandatory technical regulation in public buildings in Brazil. Presenting a solution to assist in the decision making of engineers, architects or building managers for the optimal arrangements’ choice for lighting and air conditioning equipment, considering each built environment and project profile. For the validation process, a basic building was created with 15 rooms spread over three floors, according to the most common construction parameters in the North of Brazil. First, different combinations of objective-function candidates were investigated to compose the multi-objective algorithm fitness function, analyzing its performance in two central scenarios: (1) adding some “baits” in air conditioning equipment files, and (2) without this inclusion. Thus, it was found that considering only three objective functions—incremental cost, energy consumption and the air conditioning energy efficiency coefficient—it is possible to get optimal non-dominated solutions in both scenarios, thus highlighting the robustness of the proposed methodology.

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Section: Envelopementioning

confidence: 99%

Methodology for Energy Efficiency on Lighting and Air Conditioning Systems in Buildings Using a Multi-Objective Optimization Algorithm

Monteiro

Tostes

et al. 2020

Energies

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“…There are many multi-objective optimisation (MOO) algorithms, which have different types of approach, and most of them require at least two conflicting objective functions to operate [41], [42]. This study employed an elitism MOO algorithm called non-dominated sorting genetic algorithm II (NSGA-II), which was developed by Deb et al [43].…”

Section: Multi-objective Optimisationmentioning

confidence: 99%

Computational Bim for Green Retrofitting of the Existing Building Envelope

Lim¹,

Seghier²,

Harun³

et al. 2019

WIT Transactions on the Built Environment

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Green retrofit is crucial to turning existing buildings into green buildings, but its design and analysis process is dependent on numerous disjointed methods. Various decisions are required to optimise the building efficiency, such as the choices of building materials, opening sizes, and glazing types. Therefore, this study explores the application of computational building information modelling (BIM) to automate the process of design decision-making for green retrofitting of the existing building envelope. A BIM tool (Revit), a visual programming tool (Dynamo) and multi-objective optimisation algorithm were integrated to create a computational BIM-based method for building envelope retrofitting by optimising overall thermal transfer value (OTTV) and construction investment cost. The proposed model was validated through a case study; the results showed that the optimised design achieved 44.78% reduction in OTTV with investment costs of RM (Malaysian ringgit) 369,182. The newly formulated computational BIM-based approach can improve the level of automation in green retrofitting design decision-making.

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“…Multi objective optimization (MOO) has more complex implementations and constraints compared to single objective optimization. There are many MOO algorithms which has different types of approach, and most of them require at least two conflicting objective functions to operate [18,19].…”

Section: Multi Objective Optimizationmentioning

confidence: 99%

Computational BIM for Building Envelope Sustainability Optimization

et al. 2019

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Building envelope plays an important role to protect a building from external climatic factors while providing a comfortable indoor environment. However, the choices of construction materials, opening sizes, and glazing types for optimized sustainability performance require discrete analyses and decision-making processes. Thereby this study explores the use of computational building information modelling (BIM) to automate the process of design decision-making for building envelope sustainability optimization. A BIM tool (Revit), a visual programming tool (Dynamo) and multi objective optimization algorithm were integrated to create a computational BIM-based optimization model for building envelope overall thermal transfer value (OTTV) and construction cost. The proposed model was validated through a test case; the results showed that the optimized design achieved 44.78% reduction in OTTV but 19.64% increment in construction cost compared to the original design. The newly developed computational BIM optimization model can improve the level of automation in design process for sustainability.

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Optimization of green building design to achieve green building index (GBI) using genetic algorithm (GA)

Cited by 7 publications

References 10 publications

Methodology for Energy Efficiency on Lighting and Air Conditioning Systems in Buildings Using a Multi-Objective Optimization Algorithm

Methodology for Energy Efficiency on Lighting and Air Conditioning Systems in Buildings Using a Multi-Objective Optimization Algorithm

Computational Bim for Green Retrofitting of the Existing Building Envelope

Computational BIM for Building Envelope Sustainability Optimization

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