A hybrid Decision Support System for Generation of Holistic Renovation Scenarios—Cases of Energy Consumption, Investment Cost, and Thermal Indoor Comfort

Aliakbar Kamari, Stefan Jensen, Maria Leonhard Christensen, Steffen Petersen and Poul Henning Kirkegaard
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Aliakbar Kamari: Department of Engineering, Aarhus University, 8000 Aarhus, Denmark
Stefan Jensen: Department of Engineering, Aarhus University, 8000 Aarhus, Denmark
Maria Leonhard Christensen: Department of Engineering, Aarhus University, 8000 Aarhus, Denmark
Steffen Petersen: Department of Engineering, Aarhus University, 8000 Aarhus, Denmark
Poul Henning Kirkegaard: Department of Engineering, Aarhus University, 8000 Aarhus, Denmark

Sustainability, 2018, vol. 10, issue 4, 1-23

Abstract: Future building renovations must rely on a holistic perspective in relation to sustainability. This paper presents a Decision Support Systems (DSS) that can be used by architects and engineering consultants to generate and evaluate the sustainability of renovation scenarios in a holistic manner during the early design stage of renovation projects. Firstly, this paper discusses both the notion of a sustainable renovation, together with various renovation approaches, towards the appreciation of the developing DSS for the generation of holistic scenarios. Secondly, it provides details about the mechanism and types of Multiple Criteria Decision Making methods to be exploited in the main body of the DSS. As such, a hybrid approach including a search algorithm with the Genetic Algorithm is used to combine and develop countless optimal scenarios. The performance of the generated scenarios is simulated and evaluated in terms criteria for Energy Consumption , Investment Cost , and Thermal Indoor Comfort . The trade-off between the criteria is addressed using the Pareto-front approach, and subsequently, the optimal scenarios are determined and selected using MCDM-based rating methods. The outcome is verified discussing a case study about an actual [recently] renovated dwelling and the top ranked generated scenarios using the DSS in this paper.

Keywords: building renovation; sustainable renovation; decision support systems (DSS); holistic renovation scenarios; multiple criteria decision making (MCDM); genetic algorithms (GA); energy consumption; investment cost; thermal indoor comfort (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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