Model to Assess the Intelligence Level of Buildings in the Hotel Industry by Applying Integrated Fuzzy Shannon Entropy and Fuzzy Multi-Objective Optimization on the Basis of Ratio Analysis

The rapid evolution of smart building technologies has transformed the hotel industry, necessitating structured methodologies for evaluating building intelligence. This research, dedicated to engineering problems, proposes an integrated decision-making model that combines fuzzy Shannon entropy and fuzzy multi-objective optimization on the basis of ratio analysis (MOORA) to assess the intelligence level of buildings within the hospitality sector. The model systematically determines the relative importance of intelligence criteria, including engineering, environmental, economic, social and cultural, technological, and energy conservation criteria. By leveraging fuzzy Shannon entropy, the framework objectively assigns weights to criteria based on information distribution, minimizing subjective biases in evaluation. Fuzzy MOORA is then applied to rank alternative intelligent buildings in hotels, ensuring an accurate comparative assessment. The proposed model is tested on real-world hotel data, demonstrating its effectiveness in identifying optimal intelligent building configurations. The results of applying fuzzy Shannon entropy reveal that human comfort, the emission of greenhouse gases (pollution), and system integration are the most important sub-criteria. Finally, by applying the importance of the criteria in the fuzzy MOORA model, the intelligence levels of hotels are evaluated. The results show that the Parsian Kowsar, Piroozy and Sepahan Hotels are the best hotels based on the intelligent building criteria.