Volume 14 , Issue 1 , PP: 138-148, 2024 | Cite this article as | XML | Html | PDF | Full Length Article
Esteban López E. 1 * , Silvio Machuca Vivar 2 , Luis Molina Chalacan 3
Doi: https://doi.org/10.54216/FPA.140112
Energy policy implementation relies heavily on assessing savings from retrofitting for energy efficiency. Because of their unique purpose, hospitals need energy-efficient renovations to improve indoor air quality and create a pleasant space for staff and visitors. Because of this crucial distinction, investors' preferences must be considered when deciding on refurbishment plans. Considering elements including energy savings, financial viability, and thermal comfort, this research provides a multi-criteria decision-making (MCDM) approach to guide investors in choosing the most effective remodeling plan for hospital wards. We used the MABAC method as an MCDM fusion method to combine the various criteria and alternatives to select the best one. We used ten criteria and ten alternatives in this study. We compute the weights of criteria to rank the criteria. Then, we used the MABAC fusion to rank the alternatives. The results show the financial viability has the least weight and the building envelope has the highest. We conducted a sensitivity analysis to show the stability of the results in this study.
MCDM Fusion , MABAC Fusion , Energy , Hospital Wards , Remodeling
[1] Y. Shi, R. Wang, and P. Chen, “Multi-criteria decision-making approach for energy-efficient renovation strategies in hospital wards: Balancing energy, economic, and thermal comfort,” Energy and Buildings, vol. 298, p. 113575, 2023.
[2] Y. Zhu and Y. Zhou, “Study on Sustainable Development Oriented Community Public Hospital in China Based on Optimal Decision Making Model for Environment Renovation,” Sustainability, vol. 15, no. 9, p. 7184, 2023.
[3] C. Cubukcuoglu, P. Nourian, M. F. Tasgetiren, I. S. Sariyildiz, and S. Azadi, “Hospital layout design renovation as a Quadratic Assignment Problem with geodesic distances,” Journal of Building Engineering, vol. 44, p. 102952, 2021.
[4] E. S. Mousavi and D. Bausman, “Renovation in hospitals: Pressurization strategies by healthcare contractors in the United States,” HERD: Health Environments Research & Design Journal, vol. 13, no. 1, pp. 179–190, 2020.
[5] E. Bingham, D. Whitaker, J. Christofferson, and J. Weidman, “Evidence-based design in hospital renovation projects: a study of design implementation for user controls,” HERD: Health Environments Research & Design Journal, vol. 13, no. 2, pp. 133–142, 2020.
[6] J. Gaspari, K. Fabbri, and L. Gabrielli, “A study on parametric design application to hospital retrofitting for improving energy savings and comfort conditions,” Buildings, vol. 9, no. 10, p. 220, 2019.
[7] S. Luo and W. Liang, “Optimization of roadway support schemes with likelihood-based MABAC method,” Applied Soft Computing, vol. 80, pp. 80–92, 2019.
[8] R. Lukić, “Application of MABAC method in evaluation of sector efficiency in Serbia,” Revista de Management Comparat Internațional, vol. 22, no. 3, pp. 400–418, 2021.
[9] A. Sleem, N. Mostafa, and I. Elhenawy, “Neutrosophic CRITIC MCDM Methodology for Ranking Factors and Needs of Customers in Product’s Target Demographic in Virtual Reality Metaverse,” Neutrosophic Systems with Applications, vol. 2, pp. 55–65, 2023.
[10] G. Wei, Y. He, F. Lei, J. Wu, and C. Wei, “MABAC method for multiple attribute group decision making with probabilistic uncertain linguistic information,” Journal of Intelligent & Fuzzy Systems, vol. 39, no. 3, pp. 3315–3327, 2020.
[11] J. Gong, Q. Li, L. Yin, and H. Liu, “Undergraduate teaching audit and evaluation using an extended MABAC method under q‐rung orthopair fuzzy environment,” International Journal of Intelligent Systems, vol. 35, no. 12, pp. 1912–1933, 2020.
[12] E. E. Karsak and M. Dursun, “An integrated fuzzy MCDM approach for supplier evaluation and selection,” Computers & Industrial Engineering, vol. 82, pp. 82–93, 2015.
[13] Q. He et al., “Feasibility study of a multi-criteria decision-making based hierarchical model for multi-modality feature and multi-classifier fusion: Applications in medical prognosis prediction,” Information Fusion, vol. 55, pp. 207–219, 2020.
[14] A. Madhuri, Veerapaneni Esther Jyothi, S. Phani Praveen, Mustafa Altaee, Ibrahim N. Abdullah, Granulation-Based Data Fusion Approach for a Critical Thinking Worldview Information Processing, Journal of Intelligent Systems and Internet of Things, Vol. 9 , No. 1 , (2023) : 49-68 (Doi : https://doi.org/10.54216/JISIoT.090104)
[15] M. Zhao, G. Wei, X. Chen, and Y. Wei, “Intuitionistic fuzzy MABAC method based on cumulative prospect theory for multiple attribute group decision making,” International Journal of Intelligent Systems, vol. 36, no. 11, pp. 6337–6359, 2021.
[16] X. Peng and Y. Yang, “Pythagorean fuzzy Choquet integral based MABAC method for multiple attribute group decision making,” International Journal of Intelligent Systems, vol. 31, no. 10, pp. 989–1020, 2016.
[17] Ahmed Abdelhafeez,Myvizhi M., Neutrosophic MCDM Model for Assessment Factors of Wearable Technological Devices to Reduce Risks and Increase Safety: Case Study in Education, International Journal of Advances in Applied Computational Intelligence, Vol. 3 , No. 1 , (2023) : 41-52 (Doi : https://doi.org/10.54216/IJAACI.030104)
[18] M. Abouhawwash and M. Jameel, “Evaluation Factors of Solar Power Plants to Reduce Cost Under Neutrosophic Multi-Criteria Decision-Making Model,” Sustainable Machine Intelligence Journal, vol. 2, 2023.
[19] Y. Deng, F. T. S. Chan, Y. Wu, and D. Wang, “A new linguistic MCDM method based on multiple-criterion data fusion,” Expert systems with Applications, vol. 38, no. 6, pp. 6985–6993, 2011.
[20] Ahmed Abdelhafeez, Hoda K. Mohamed, Skin Cancer Detection using Neutrosophic c-means and Fuzzy c-means Clustering Algorithms, Journal of Intelligent Systems and Internet of Things, Vol. 8 , No. 1 , (2023) : 33-42 (Doi : https://doi.org/10.54216/JISIoT.080103).
[21] J. J. H. Liou and G.-H. Tzeng, “Comments on ‘Multiple criteria decision making (MCDM) methods in economics: an overview,’” Technological and Economic Development of Economy, vol. 18, no. 4, pp. 672–695, 2012.
[22] Alber S. Aziz, Neutrosophic Combinative Distance-based Assessment (CODAS) Method for Evaluating the Financial and Operational Performance of Shipping Companies, International Journal of Advances in Applied Computational Intelligence, Vol. 4 , No. 1 , (2023) : 28-36 (Doi : https://doi.org/10.54216/IJAACI.040103)
[23] D. Pamučar, I. Petrović, and G. Ćirović, “Modification of the Best–Worst and MABAC methods: A novel approach based on interval-valued fuzzy-rough numbers,” Expert systems with applications, vol. 91, pp. 89–106, 2018.
[24] D. Pamučar and G. Ćirović, “The selection of transport and handling resources in logistics centers using Multi-Attributive Border Approximation area Comparison (MABAC),” Expert systems with applications, vol. 42, no. 6, pp. 3016–3028, 2015.
[25] A. M. AbdelMouty and A. Abdel-Monem, “Neutrosophic MCDM Methodology for Assessment Risks of Cyber Security in Power Management,” Neutrosophic Systems with Applications, vol. 3, pp. 53–61, 2023.
[26] A. Alinezhad, J. Khalili, A. Alinezhad, and J. Khalili, “MABAC method,” New Methods and Applications in Multiple Attribute Decision Making (MADM), pp. 193–198, 2019.
[27] R. Sun, J. Hu, J. Zhou, and X. Chen, “A hesitant fuzzy linguistic projection-based MABAC method for patients’ prioritization,” International Journal of Fuzzy Systems, vol. 20, pp. 2144–2160, 2018.
[28] A. E. Torkayesh, E. B. Tirkolaee, A. Bahrini, D. Pamucar, and A. Khakbaz, “A systematic literature review of MABAC method and applications: An outlook for sustainability and circularity,” Informatica, vol. 34, no. 2, pp. 415–448, 2023.
[29] G. Wei, C. Wei, J. Wu, and H. Wang, “Supplier selection of medical consumption products with a probabilistic linguistic MABAC method,” International Journal of Environmental Research and Public Health, vol. 16, no. 24, p. 5082, 2019.