Energy in context: A multicriteria model for building design

Gero, John S.; D'cruz, Neville; Radford, Antony

doi:10.1016/0360-1323(83)90001-x

Cited by 72 publications

(33 citation statements)

References 6 publications

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“…These methodologies can be categorized into two main approaches: the models in which alternative retrofit solutions are explicitly known a priori (see e.g. [11], [12], [13], [14]) and the models in which alternative retrofit solutions are implicitly defined in the setting of an optimization model (see e.g. [7], [15], [16], [17]).…”

Section: Literature Reviewmentioning

confidence: 99%

“…It is then possible to find the single design solution that optimizes the weighted sum of the criteria. Gero et al [11] were among the first to propose a multi-criteria analysis (MCA) model to be used at the process of building design in order to explore the trade-offs between the building thermal performance and other criteria such as capital cost and usable area. More recently, other researchers have also employed MCA techniques to similar problems.…”

Section: Literature Reviewmentioning

confidence: 99%

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Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application

Asadi

Silva

Antunes

et al. 2014

Energy and Buildings

404

155

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Page 2 of 46 A c c e p t e d M a n u s c r i p t 2 Retrofitting of existing buildings offers significant opportunities for improving occupants' comfort and well-being, reducing global energy consumption and greenhouse gas emissions. This is being considered as one of the main approaches to achieve sustainability in the built environment at relatively low cost and high uptake rates. Although a wide range of retrofit technologies is readily available, methods to identify the most suitable set of retrofit actions for particular projects are still a major technical and methodological challenge. This paper presents a multi-objective optimization model using genetic algorithm (GA) and artificial neural network (ANN) to quantitatively assess technology choices in a building retrofit project. This model combines the rapidity of evaluation of ANNs with the optimization power of GAs. A school building is used as a case study to demonstrate the practicability of the proposed approach and highlight potential problems that may arise. The study starts with the individual optimization of objective functions focusing on building's characteristics and performance: energy consumption, retrofit cost, and thermal discomfort hours. Then a multi-objective optimization model is developed to study the interaction between these conflicting objectives and assess their trade-offs.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application

Asadi

Silva

Antunes

et al. 2014

Energy and Buildings

404

155

View full text Add to dashboard Cite

show abstract

“…Pareto optimization was introduced in the 1980s by Radford, Gero and D'Cruz [31][32][33][34], and it is now widely used in building design optimization [10,14,35]. It was used, for example, by Wang et al [19] to optimize ''green" buildings according to life-cycle exergetic assessment and costs, and by Verbeeck and Hens [36] to minimize the global warming potential of low-energy dwellings, with a particular focus on energy consumption and construction costs.…”

Section: Existing Approaches To Multicriteria Analysismentioning

confidence: 99%

Development of a multicriteria tool for optimizing the renovation of buildings

et al. 2011

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“…However, it is then necessary to reach a final compromise solution for practical implementation of a reduced set of non-dominated solutions for further screening. Pareto optimization was introduced in this area in the 1980s by Radford and Gero (1980a, b), Gero et al (1983), D'cruz and Radford (1987), and it is now widely used in building design and less in retrofit optimization. It was used, for example, by Asadi et al (2012a, b) to optimize the retrofit cost and energy savings of a residential building.…”

Section: Multi-objective Programming (Mop) Approachesmentioning

confidence: 99%

State of the Art on Retrofit Strategies Selection Using Multi-objective Optimization and Genetic Algorithms

Asadi

Silva

Antunes

et al. 2013

Nearly Zero Energy Building Refurbishment

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The retrofit of a building involves not just the fulfillment of functional requirements, but also considerations such as investment costs, energy consumption, environmental impact, and occupant well-being. Careful long-term decisions in the retrofit and operation of buildings can significantly improve their thermal performance and thus reduce their consumption of energy. Moreover, they can improve indoor environmental quality in buildings. Alternative building energy conservation measures, standards compliance, and economic optimization can be evaluated using available energy analysis and decision-aid techniques. These may range from simplified energy analysis methods for approximate energy use estimates to detailed computerized hourly simulation coupled with decision-aid techniques. This chapter reviews the research and development in the decision support processes in building retrofit. Special attention is devoted to the methodologies using multi-objective optimization and genetic algorithms. Accordingly, the decision methodologies are broadly separated into two main categories: approaches in which alternatives are explicitly known a priori and approaches in which alternatives are implicitly defined by an optimization model. The advantages and drawbacks of the various methods in each category are also discussed.

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Energy in context: A multicriteria model for building design

Cited by 72 publications

References 6 publications

Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application

Multi-objective optimization for building retrofit: A model using genetic algorithm and artificial neural network and an application

Development of a multicriteria tool for optimizing the renovation of buildings

State of the Art on Retrofit Strategies Selection Using Multi-objective Optimization and Genetic Algorithms

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