Multi-Criteria Evaluation of Building Design Alternatives for Energy Efficiency Using CRITIC and CoCoSo Methods

Abstract

This study aims to evaluate building design alternatives in terms of energy efficiency using the Multi-Criteria Decision-Making (MCDM) approach. The analysis was conducted on 12 representative building alternatives selected from the UCI Energy Efficiency dataset using the K-Means clustering algorithm. Relative compactness, surface area, wall area, roof area, overall height, and glazing area design parameters were selected as criteria. The criterion weights were objectively determined using the CRITIC (Criteria Importance Through Intercriteria Correlation) method, which takes into account inter-criteria correlation and data variability. The CoCoSo (Combined Compromise Solution) method was used to rank the building alternatives. As a result of the analysis, the ranking results of the building alternatives were compared with the reference Heating Load and Cooling Load indicators, and it was observed that the alternatives with higher performance scores exhibited better energy performance. As a result, the proposed CRITIC-CoCoSo approach provides an objective, reliable, and data-driven decision support tool for the evaluation of building energy performance.