Prioritizing criteria for selecting advanced technologies for martian smart buildings: A fuzzy Delphi study using the VIKOR method
Year: 2025
Type: article
Abstract: This study aimed to identify and rank essential criteria and sub-criteria for designing and implementing smart buildings in harsh settings such as Mars. During the first stage, the Delphi fuzzy approach was used to create a questionnaire and analyze the responses of ten experts. This resulted in the elimination of a number of less important criteria and sub-criteria. The remaining groups, including the criteria and sub-criteria, were weighted using the AHP pairwise comparison approach. The VIKOR approach was used to rank the criteria and make final decisions. The findings revealed that parameters such as protection from cosmic radiation and hazardous rays, high energy conversion efficiency, and the cost of creating nanomaterials were highly prioritized in both techniques and chosen as the most essential criteria for enhancing smart buildings. There were some discrepancies in criteria ranking between the AHP and VIKOR methodologies. The findings revealed that thermal insulation to limit heat transmission, as well as emergency energy and water storage systems in VIKOR, outperformed AHP. These discrepancies are due to how the distance from the ideal is calculated, and VIKOR emphasizes boundary conditions when evaluating the criteria. These analyses showed that combining these two methods can provide comprehensive perspectives for decision-making. Also, future research suggests that simulation of real Mars conditions and sensitivity analysis will help decision-makers achieve more accurate priorities. However, new criteria such as resilience of systems to failure, use of local resources in construction, and psychological effects of interior design should be added to this framework using hybrid methods such as TOPSIS and DEA or combining multi-criteria methods that provide more accurate results.
Source: Space habitation.
Author: Amirhossein Javaherikhah
Institution: Universidad Politécnica de Madrid
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
Estimated APC paid:
OpenAlex ID: W7116097564