4.7 Article

Decision Support System for technology selection based on multi-criteria ranking: Application to NZEB refurbishment

Journal

BUILDING AND ENVIRONMENT
Volume 212, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.buildenv.2022.108786

Keywords

Decision Support System (DSS); Multi-Criteria Decision-Making(MCDM); Dynamic User Interface (UI); Sensitivity analysis; Decision under uncertainty

Funding

  1. European Union [768623]
  2. H2020 Societal Challenges Programme [768623] Funding Source: H2020 Societal Challenges Programme

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This study proposes a Decision Support System based on Multi-Criteria Decision-Making for selecting technologies in building refurbishment. The system allows Decision Makers to browse the solutions space, specify criteria preferences, and assess technologies based on different variables. It is implemented and validated through a use case concerning the choice of insulating materials.
Refurbishing existing building into Near Zero Energy Building (NZEB) is a key objective for the European Union. In order to achieve high rate of conversion, new refurbishment process must allow Decision Makers (DMs) (architects or designers) to sort through an ever increasing list of new technologies while taking into account uncertain preferences from multiple stakeholders. A Decision Support System (DSS) based on Multi-Criteria Decision-Making (MCDM) approaches is proposed. The DSS enables the DMs to browse the solutions space by selecting the relevant criteria, order them by preferences and specify the granularity in the assessment of the technologies regarding each criteria. This DSS is based on a ranking algorithm that operates on multiple types of quantitative (continuous, discrete, or binary) and qualitative (nominative or ordinal) variables from technological and human sources. An online user interface allows the real-time exploration of the solution space. A sensitivity analysis of the algorithm is conducted to expose the influence of the ranking algorithm parameters and to demonstrate the robustness of this algorithm. The proposed DSS is eventually implemented and validated through a use case concerning the choice of insulating materials considering heterogeneous criteria that model sustainable constraints.

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