3054. Towards a DSS for Selecting Sustainable Construction Materials Using Multi-Criteria Models
Invited abstract in session TA-8: Hierarchical MCDA and MCDA in circular economy, stream Multiple Criteria Decision Aiding.
Tuesday, 8:30-10:00Room: Clarendon SR 2.08
Authors (first author is the speaker)
| 1. | Nikos Tsotsolas
|
| Business Administration, Univeristy of West Attica | |
| 2. | Athanasios Spyridakos
|
| Department of Business Administration, University of West Attica | |
| 3. | Isaak Vryzidis
|
| Laboratory of Geoenvironmental Science & Environmental Quality Assurance, Department of Civil Engineering, University of West Attica |
Abstract
In recent years, the construction industry has highlighted the increased need to improve resource efficiency, reduce waste and increase value through the selection of sustainable construction materials. Given that fact that waste materials from construction and demolition activities make up over a third of all waste in the EU, the reuse of materials from existing buildings to supply new construction and renovation projects has the potential to reduce demolition waste, as well as demand for primary (non-recycled) materials and greenhouse gas emissions. The basic concept of sustainable building construction and retrofitting is to maximize value and minimize cost by achieving a balance between social, economic, technical and environmental aspects. As part of a research project, a DSS is being developed that will address decisions related to the selection of the optimal construction materials per project, based on life cycle assessment (LCA), life cycle costing (LCC) and social assessment (S-LCA) criteria. The DSS integrates two MCDA methods, namely WAP and Stochastic UTAdis. Through the application of these methods, the grading (value) will be elicited and the classification of the materials will be produced. This documented information could be included, in accordance with EU guidelines, in the Digital Passport of Building Materials, which will act as a tool to enhance transparency and sustainability in the construction industry.
Keywords
- OR in Sustainability
- Machine Learning
- Decision Support Systems
Status: accepted
Back to the list of papers