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

TY - JOUR

T1 - A hybrid Decision Support System for Generation of Holistic Renovation Scenarios - Cases of Energy Consumption, Investment Cost, and Thermal Indoor Comfort

AU - Kamari, Aliakbar

AU - Jensen, Stefan

AU - Leonhard Christensen, Maria

AU - Petersen, Steffen

AU - Kirkegaard, Poul Henning

N1 - This article belongs to the Special Issue Sustainable Building Renovation

PY - 2018/4/19

Y1 - 2018/4/19

N2 - 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-offbetween 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.

AB - 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-offbetween 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.

KW - Building renovation

KW - Decision support systems (DSS)

KW - Energy consumption

KW - Genetic algorithms (GA)

KW - Holistic renovation scenarios

KW - Investment cost

KW - Multiple criteria decision making (MCDM)

KW - Sustainable renovation

KW - Thermal indoor comfort

U2 - 10.3390/su10041255

DO - 10.3390/su10041255

M3 - Journal article

SN - 2071-1050

VL - 10

JO - Sustainability

JF - Sustainability

IS - 4

M1 - 1255

ER -