Decision support system (DSS) for selecting sustainable insulation material using Pareto search and novel fuzzy-modified technique for order of preference by similarity to ideal solution (TOPSIS) approach

Efforts to improve the sustainability of the building construction sector have tended to focus on reducing operational energy cost, whereas sustainability considerations in the material selection at the design and construction phase have received less attention due to construction budget constraints. The present study proposes a decision support system (DSS) to assist decision-makers in accounting for sustainability in their construction material selections. We demonstrate how the developed DSS can be used to identify the most sustainable insulation materials and thicknesses among commercially available alternatives. The DSS ranks available alternatives by incorporating individual project information, material information, and the decision maker’s preferences. Technique for order of preference by similarity to ideal solution (TOPSIS) and Pareto search technique are combined in the methodology. By limiting the alternatives to the 'Pareto front' of life cycle assessment (LCA) and life cycle cost in a multi-objective optimization setting, we seek to reduce subjectivity in the multi-criterion decision-making process. Moreover, product-specific environmental product declaration is used to calculate the embodied energy for the LCA. The framework recommends commercially available materials and thicknesses accordingly. The proposed method is programmed in Python to establish a user interface for data input and output of results.