A Hybrid Multi-criteria Decision-making and Allocation Model for Selection of Hospital Waste Disposal Firms
Subject Areas : wasteMohammad amin Sabeti Karajvandani 1 , Ghasem Abbasi 2 , Omid Amirtaheri 3 , Soheila Khishtandar 4 *
1 - Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
2 - Department of Mathematics, Qazvin Branch, Islamic Azad University, Qazvin, Iran.
3 - Department of Industrial Management, Shahid Beheshti University, Tehran, Iran.
4 - ¬¬Department of Industrial Management, Qazvin Branch, Islamic Azad University, Qazvin, Iran. *(Corresponding Author)
Keywords: Waste Management, Hospital Waste Disposal, Single and Multiple Outsourcing.,
Abstract :
Background and Objective: In a context where substantial volumes of hospital waste are generated and disposed of daily, the ineffective sanitary disposal of such waste can lead to environmental risks and higher operational expenses. However, hospitals frequently overlook objective criteria when evaluating and selecting waste disposal firms, relying instead on subjective judgment and past experiences. This research proposes a decision-making framework that presents a hybrid model combining multi-criteria decision-making and linear programming. The primary objective of this study is to propose a safe and efficient method for outsourcing disposing of or recycling hospital waste. Material and Methodology: This study presents a framework for decision-making in hospital waste disposal, addressing both single and multiple outsourcing scenarios. Firstly, the literature is reviewed to identify the criteria for evaluating waste disposal firms. The DEMATEL method is employed to explore the cause-and-effect relationships among these criteria, selecting the most significant ones and visualizing their causal relationships in a network format. The analytic network process (ANP) method is then utilized to evaluate and choose the most suitable waste disposal firm in a single outsourcing scenario. Additionally, to mitigate the risks associated with single outsourcing, a linear programming model is introduced for multiple outsourcing. This mathematical model determines the optimal allocation of waste quantities to various waste disposal firms, aiming to maximize the overall amount of waste disposed of by these firms. Fidings: The framework introduced in this study was put into practice to assess and choose hospital waste disposal firms in Tehran. Through a comprehensive literature review, 10 evaluation criteria were identified. Among these, the six most influential criteria were selected using the DEMATEL method, and their causal relationships were depicted in a network. The ANP was employed to assign weights to the evaluation criteria and the candidate firms. The evaluation criteria, in descending order of importance, include qualified human resources, recycling and disposal capacity, experience, cost, collection and transportation infrastructure, and waste disposal and recycling technology. Furthermore, a linear programming model was solved using Lingo software to optimize the allocation of waste among the candidate firms. Discussion & Conclusion: The decision-making model presented in this article offers advantages to both hospital officials and urban pollution control officials in the context of outsourcing sanitary waste disposal. The outcomes obtained from implementing the proposed framework demonstrate that decision-making based on this model not only benefits hospitals in selecting a suitable firm but also helps to mitigate conflicts of interest and disagreements between hospitals, sanitary waste disposal firms, and urban pollution control officials.
1. Saeb, K., Kardar, S., Salehi, F., & Alidoust, S. (2017). Assessment of Hospital Waste Management system with focus on disinfection method. Journal of Environmental Science and Technology, 19(3), 113-127. doi: 10.22034/jest.2017.11073 (In Persian)
2. Chen, C., Chen, J., Fang, R., Ye, F., Yang, Z., Wang, Z., Shi, F., & Tan, W. (2021). What medical waste management system may cope with COVID-19 pandemic: Lessons from Wuhan. Resources, conservation, and recycling, 170, 105600. doi: 10.1016/j.resconrec.2021.105600
3. Gitipour, S., Akbarpoursareskanroud, F., & Firouzbakht, S. (2017). Assessment of Medical Waste in Tehran Province Hospitals. Journal of Environmental Studies, 42(4), 709-718. doi: 10.22059/jes.2017.60936 (In Persian)
4. Hsu, P., Wu, C., & Li, Y. (2008). Selection of infectious medical waste disposal firms by using the analytic hierarchy process and sensitivity analysis, Waste Management, 28(8),1386-1394. doi: 10.1016/j.wasman.2007.05.016.
5. Seikh, M. R., & Mandal, U. (2023). Interval-valued Fermatean fuzzy Dombi aggregation operators and SWARA based PROMETHEE II method to bio-medical waste management, Expert Systems with Applications, 226,120082, doi: 10.1016/j.eswa.2023.120082.
6. Görçün, Ö. F., Aytekin, A., Korucuk, S., & Tirkolaee, E. B. (2023). Evaluating and selecting sustainable logistics service providers for medical waste disposal treatment in the healthcare industry. Journal of Cleaner Production, 408, 137194. doi: 10.1016/j.jclepro.2023.137194
7. Kaya, İ. (2012). Evaluation of outsourcing alternatives under fuzzy environment for waste management. Resources, Conservation and Recycling, 60, 107-118. doi: 10.1016/j.resconrec.2011.12.006
8. Çelik, S., Peker, İ., Gök-Kısa, A. C., & Büyüközkan, G. (2023). Multi-criteria evaluation of medical waste management process under intuitionistic fuzzy environment: A case study on hospitals in Turkey. Socio-Economic Planning Sciences, 86, 101499. doi: 10.1016/j.seps.2022.101499
9. Liu, P., Rani, P., & Mishra, A. R. (2021). A novel Pythagorean fuzzy combined compromise solution framework for the assessment of medical waste treatment technology. Journal of Cleaner Production, 292, 126047. doi: 10.1016/j.jclepro.2021.126047
10. Tushar, S. R., Alam, M. F. B., Bari, A. M., & Karmaker, C. L. (2023). Assessing the challenges to medical waste management during the COVID-19 pandemic: Implications for the environmental sustainability in the emerging economies. Socio-Economic Planning Sciences, 101513. doi: 10.1016/j.seps.2023.101513
11. Ho, C. C. (2011). Optimal evaluation of infectious medical waste disposal companies using the fuzzy analytic hierarchy process. Waste management, 31(7), 1553-1559.
12. Gumus, A. T. (2009). Evaluation of hazardous waste transportation firms by using a two-step fuzzy-AHP and TOPSIS methodology. Expert systems with applications, 36(2), 4067-4074. doi: 10.1016/j.eswa.2008.03.013
13. Modiri, M. (2020). Ranking of hospital waste disposal outsourcing companies with the new fuzzy multiple criteria decision-making hybrid method and grey. Modern Research in Decision Making, 5(1), 1-23. (In Persian)
14. Mardani S, Alimohammadzade K, Maher A, Hoseini S., & Yaghmaeian K. (2019). Ranking the hospitals in terms of hospital waste reduction criteria case study: educational hospitals of Shahid Beheshti University of Medical Sciences (SBUMS). Iranianian Journal of Health and Environment, 12 (2), 217-234. (In Persian)
15. Manupati, V. K., Ramkumar, M., Baba, V., & Agarwal, A. (2021). Selection of the best healthcare waste disposal techniques during and post COVID-19 pandemic era. Journal of cleaner production, 281, 125175. doi: 10.1016/j.jclepro.2020.125175
16. Liao, C. J., & Ho, C. C. (2014). Risk management for outsourcing biomedical waste disposal–Using the failure mode and effects analysis. Waste management, 34(7), 1324-1329. doi: 10.1016/j.wasman.2014.03.007
17. El Mokrini, A., & Aouam, T. (2022). A decision-support tool for policy makers in healthcare supply chains to balance between perceived risk in logistics outsourcing and cost-efficiency. Expert Systems with Applications, 201, 116999. doi: 10.1016/j.eswa.2022.116999
18. Tirkolaee, E. B., Abbasian, P., & Weber, G. W. (2021). Sustainable fuzzy multi-trip location-routing problem for medical waste management during the COVID-19 outbreak. Science of the Total Environment, 756, 143607. doi: 10.1016/j.scitotenv.2020.143607
19. Babaee Tirkolaee, E., & Aydın, N. S. (2021). A sustainable medical waste collection and transportation model for pandemics. Waste Management & Research, 39, 34-44. doi: 10.1177/0734242X211000437
20. Chauhan, A., & Singh, S. P. (2021). Selection of healthcare waste disposal firms using a multi-method approach. Journal of Environmental Management, 295, 113117. doi: 10.1016/j.jenvman.2021.113117
21. Tzeng, G. H., & Huang, J. J. (2011). Multiple attribute decision making: methods and applications. CRC press.
22. Torkashvand, J., Farzadkia, M., Jonidi Jafari, A., Heidari, M., & Ghalkhanbaz, A. (2019). Comparison and Prioritization of the Different Disinfection Methods of Infectious Waste. Journal of Research in Environmental Health, 5(3), 194-204. doi: 10.22038/jreh.2019.41016.1310 (In Persian)