A Goal Programming Based Bi-Stage Network Design for COVID-19 Immunization Waste Management

Document Type : Research Paper

Authors

1 O.P. Jindal Global University Sonipat

2 O. P. Jindal Global University Sonipat, India

3 Department of Industrial and Production Engineering, Bangladesh University of Engineering and Technology, Dhaka-1000, Bangladesh

Abstract

The recent global efforts to control the spread of highly contagious COVID-19 pandemic have been successful, largely due to extensive vaccination campaigns. However, these campaigns have generated an enormous amount of infectious medical waste. This paper presents a weighted goal programming-based optimization model for managing medical waste generated from COVID-19 vaccination efforts. The model proposes an efficient system by integrating decisions of locating treatment centers and the routing of generated waste to these centers and eventually to disposal sites, with a focus on cost reduction, risk mitigation for the environment and the nearby population. The objectives include minimizing the setup and transportation costs, reducing risks to the population, limiting the number of installed units, and ensuring environmental sustainability of disposal sites. A set of randomly selected test instances is used to test the model's effectiveness. The results indicate that the compromised solution provides both cost benefits and reduced risk to the population. Specifically, the cost objective was compromised by only 5.98% and the risk objective by 1.54%, while the environmental sustainability objective was fully achieved.  This approach effectively supports strategic choices in recycling healthcare waste generated from COVID-19 immunization. The study is expected to aid municipal managers and decision-makers of healthcare facilities in managing vaccination related waste more efficiently.

Keywords


Alshraideh, H., & Abu Qdais, H. (2017). Stochastic modeling and optimization of medical waste collection in Northern Jordan. Journal of Material Cycles and Waste Management, 19(2), 743–753. https://doi.org/10.1007/s10163-016-0474-3
Alumur, S., & Kara, B. Y. (2007). A new model for the hazardous waste location-routing problem. Computers & Operations Research, 34(5), 1406–1423. https://doi.org/10.1016/j.cor.2005.06.012
Amani Bani, E., Fallahi, A., Varmazyar, M., & Fathi, M. (2022). Designing a sustainable reverse supply chain network for COVID-19 vaccine waste under uncertainty. Computers & Industrial Engineering, 174, 108808. https://doi.org/10.1016/j.cie.2022.108808
Ardjmand, E., Weckman, G., Park, N., Taherkhani, P., & Singh, M. (2015). Applying genetic algorithm to a new location and routing model of hazardous materials. International Journal of Production Research, 53(3), 916–928. https://doi.org/10.1080/00207543.2014.942010
Asgari, N., Rajabi, M., Jamshidi, M., Khatami, M., & Farahani, R. Z. (2017). A memetic algorithm for a multi-objective obnoxious waste location-routing problem: a case study. Annals of Operations Research, 250(2), 279–308. https://doi.org/10.1007/s10479-016-2248-7
Baati, D., Mellouli, M., & Hachicha, W. (2014). Designing a new infectious healthcare-waste management system in sfax governorate, tunisia. 2014 International Conference on Advanced Logistics and Transport (ICALT), 350–355. https://doi.org/10.1109/ICAdLT.2014.6866337
Berglund, P. G., & Kwon, C. (2014). Robust Facility Location Problem for Hazardous Waste Transportation. Networks and Spatial Economics, 14(1), 91–116. https://doi.org/10.1007/s11067-013-9208-4
Bertsimas, D., Digalakis Jr, V., Jacquillat, A., Li, M. L., & Previero, A. (2022). Where to locate COVID ‐19 mass vaccination facilities? Naval Research Logistics (NRL), 69(2), 179–200. https://doi.org/10.1002/nav.22007
Budak, A., & Ustundag, A. (2017). Reverse logistics optimisation for waste collection and disposal in health institutions: the case of Turkey. International Journal of Logistics Research and Applications, 20(4), 322–341. https://doi.org/10.1080/13675567.2016.1234595
Cao, C., Liu, J., Liu, Y., Wang, H., & Liu, M. (2023). Digital twin-driven robust bi-level optimisation model for COVID-19 medical waste location-transport under circular economy. Computers & Industrial Engineering, 109107. https://doi.org/10.1016/j.cie.2023.109107
Cao, C., Xie, Y., Liu, Y., Liu, J., & Zhang, F. (2023). Two-phase COVID-19 medical waste transport optimisation considering sustainability and infection probability. Journal of Cleaner Production, 389, 135985. https://doi.org/10.1016/j.jclepro.2023.135985
Charnes, A., & Cooper, W. W. (1957). Management Models and Industrial Applications of Linear Programming. Management Science, 4(1), 38–91. https://doi.org/10.1287/mnsc.4.1.38
Chauhan, A., & Singh, A. (2016). A hybrid multi-criteria decision making method approach for selecting a sustainable location of healthcare waste disposal facility. Journal of Cleaner Production, 139, 1001–1010. https://doi.org/10.1016/j.jclepro.2016.08.098
Crommelin, D. J. A., Volkin, D. B., Hoogendoorn, K. H., Lubiniecki, A. S., & Jiskoot, W. (2021). The Science is There: Key Considerations for Stabilizing Viral Vector-Based Covid-19 Vaccines. Journal of Pharmaceutical Sciences, 110(2), 627–634. https://doi.org/10.1016/j.xphs.2020.11.015
Das, A., Mazumder, T. N., & Gupta, A. K. (2012). Pareto frontier analyses based decision making tool for transportation of hazardous waste. Journal of Hazardous Materials, 227228, 341–352. https://doi.org/10.1016/j.jhazmat.2012.05.068
Debnath, B., Bari, A. B. M. M., Ali, S. M., Ahmed, T., Ali, I., & Kabir, G. (2023). Modelling the barriers to sustainable waste management in the plastic-manufacturing industry: An emerging economy perspective. Sustainability Analytics and Modeling, 3, 100017. https://doi.org/10.1016/j.samod.2023.100017
Emek, E., & Kara, B. Y. (2007). Hazardous waste management problem: The case for incineration. Computers & Operations Research, 34(5), 1424–1441. https://doi.org/10.1016/j.cor.2005.06.011
Eren, E., & Rıfat Tuzkaya, U. (2021). Safe distance-based vehicle routing problem: Medical waste collection case study in COVID-19 pandemic. Computers & Industrial Engineering, 157, 107328. https://doi.org/10.1016/j.cie.2021.107328
Farrokhi-Asl, H., Tavakkoli-Moghaddam, R., Asgarian, B., & Sangari, E. (2017). Metaheuristics for a bi-objective location-routing-problem in waste collection management. Journal of Industrial and Production Engineering, 34(4), 239–252. https://doi.org/10.1080/21681015.2016.1253619
Flavell, R. (1976). A new goal programming formulation. Omega, 4(6), 731–732. https://doi.org/10.1016/0305-0483(76)90099-2
Gergin, Z., Tunçbilek, N., & Esnaf, Ş. (2019). Clustering Approach Using Artificial Bee Colony Algorithm for Healthcare Waste Disposal Facility Location Problem. International Journal of Operations Research and Information Systems, 10(1), 56–75. https://doi.org/10.4018/IJORIS.2019010104
Govindan, K., Nasr, A. K., Mostafazadeh, P., & Mina, H. (2021). Medical waste management during coronavirus disease 2019 (COVID-19) outbreak: A mathematical programming model. Computers & Industrial Engineering, 162, 107668. https://doi.org/10.1016/j.cie.2021.107668
Haque, M. S., Uddin, S., Sayem, S. M., & Mohib, K. M. (2021). Coronavirus disease 2019 (COVID-19) induced waste scenario: A short overview. Journal of Environmental Chemical Engineering, 9(1), 104660. https://doi.org/10.1016/j.jece.2020.104660
Hasija, V., Patial, S., Raizada, P., Thakur, S., Singh, P., & Hussain, C. M. (2022). The environmental impact of mass coronavirus vaccinations: A point of view on huge COVID-19 vaccine waste across the globe during ongoing vaccine campaigns. Science of The Total Environment, 813, 151881. https://doi.org/10.1016/j.scitotenv.2021.151881
Ho, H.-P. (2019). The supplier selection problem of a manufacturing company using the weighted multi-choice goal programming and MINMAX multi-choice goal programming. Applied Mathematical Modelling, 75, 819–836. https://doi.org/10.1016/j.apm.2019.06.001
Kargar, S., Paydar, M. M., & Safaei, A. S. (2020). A reverse supply chain for medical waste: A case study in Babol healthcare sector. Waste Management, 113, 197–209. https://doi.org/10.1016/j.wasman.2020.05.052
Kargar, S., Pourmehdi, M., & Paydar, M. M. (2020). Reverse logistics network design for medical waste management in the epidemic outbreak of the novel coronavirus (COVID-19). Science of The Total Environment, 746, 141183. https://doi.org/10.1016/j.scitotenv.2020.141183
Lee, C. K. M., Yeung, C. L., Xiong, Z. R., & Chung, S. H. (2016). A mathematical model for municipal solid waste management – A case study in Hong Kong. Waste Management, 58, 430–441. https://doi.org/10.1016/j.wasman.2016.06.017
Li, L., Wang, S., Lin, Y., Liu, W., & Chi, T. (2015). A covering model application on Chinese industrial hazardous waste management based on integer program method. Ecological Indicators, 51, 237–243. https://doi.org/10.1016/j.ecolind.2014.05.001
Manning, M. Lou, Gerolamo, A. M., Marino, M. A., Hanson-Zalot, M. E., & Pogorzelska-Maziarz, M. (2021). COVID-19 Vaccination Readiness among Nurse Faculty and Student Nurses. Nursing Outlook. https://doi.org/10.1016/j.outlook.2021.01.019
Mantzaras, G., & Voudrias, E. A. (2017). An optimization model for collection, haul, transfer, treatment and disposal of infectious medical waste: Application to a Greek region. Waste Management, 69, 518–534. https://doi.org/10.1016/j.wasman.2017.08.037
Matete, N., & Trois, C. (2008). Towards Zero Waste in emerging countries – A South African experience. Waste Management, 28(8), 1480–1492. https://doi.org/10.1016/j.wasman.2007.06.006
Nema, A. K., & Gupta, S. K. (2003). Multiobjective Risk Analysis and Optimization of Regional Hazardous Waste Management System. Practice Periodical of Hazardous, Toxic, and Radioactive Waste Management, 7(2), 69–77. https://doi.org/10.1061/(ASCE)1090-025X(2003)7:2(69)
Nolz, P. C., Absi, N., & Feillet, D. (2014). A stochastic inventory routing problem for infectious medical waste collection. Networks, 63(1), 82–95. https://doi.org/10.1002/net.21523
Osaba, E., Yang, X.-S., Fister, I., Del Ser, J., Lopez-Garcia, P., & Vazquez-Pardavila, A. J. (2019). A Discrete and Improved Bat Algorithm for solving a medical goods distribution problem with pharmacological waste collection. Swarm and Evolutionary Computation, 44, 273–286. https://doi.org/10.1016/j.swevo.2018.04.001
Paredes-Belmar, G., Bronfman, A., Marianov, V., & Latorre-Núñez, G. (2017). Hazardous materials collection with multiple-product loading. Journal of Cleaner Production, 141, 909–919. https://doi.org/10.1016/j.jclepro.2016.09.163
Rabbani, M., Heidari, R., Farrokhi-Asl, H., & Rahimi, N. (2018). Using metaheuristic algorithms to solve a multi-objective industrial hazardous waste location-routing problem considering incompatible waste types. Journal of Cleaner Production, 170, 227–241. https://doi.org/10.1016/j.jclepro.2017.09.029
Rattanawai, N., Arunyanart, S., & Pathumnakul, S. (2024). Optimizing municipal solid waste collection vehicle routing with a priority on infectious waste in a mountainous city landscape context. Transportation Research Interdisciplinary Perspectives, 24, 101066. https://doi.org/10.1016/j.trip.2024.101066
Shahparvari, S., Hassanizadeh, B., Mohammadi, A., Kiani, B., Lau, K. H., Chhetri, P., & Abbasi, B. (2022). A decision support system for prioritised COVID-19 two-dosage vaccination allocation and distribution. Transportation Research Part E: Logistics and Transportation Review, 159, 102598. https://doi.org/10.1016/j.tre.2021.102598
Shih, L.-H., & Lin, Y.-T. (2003). Multicriteria Optimization for Infectious Medical Waste Collection System Planning. Practice Periodical of Hazardous, Toxic, and Radioactive Waste Management, 7(2), 78–85. https://doi.org/10.1061/(ASCE)1090-025X(2003)7:2(78)
Taghipour, H., & Mosaferi, M. (2009). Characterization of medical waste from hospitals in Tabriz, Iran. Science of The Total Environment, 407(5), 1527–1535. https://doi.org/10.1016/j.scitotenv.2008.11.032
Tamiz, M., Jones, D., & Romero, C. (1998). Goal programming for decision making: An overview of the current state-of-the-art. European Journal of Operational Research, 111(3), 569–581. https://doi.org/10.1016/S0377-2217(97)00317-2
Tasouji Hassanpour, S., Ke, G. Y., Zhao, J., & Tulett, D. M. (2023). Infectious waste management during a pandemic: A stochastic location-routing problem with chance-constrained time windows. Computers & Industrial Engineering, 177, 109066. https://doi.org/10.1016/j.cie.2023.109066
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. https://doi.org/10.1016/j.scitotenv.2020.143607
Trivedi, A., & Singh, A. (2017). A hybrid multi-objective decision model for emergency shelter location-relocation projects using fuzzy analytic hierarchy process and goal programming approach. International Journal of Project Management, 35(5), 827–840. https://doi.org/10.1016/j.ijproman.2016.12.004
Tushar, S. R., Alam, M. F. Bin, Bari, A. B. M. 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, 87, 101513. https://doi.org/10.1016/j.seps.2023.101513
Valizadeh, J., Hafezalkotob, A., Seyed Alizadeh, S. M., & Mozafari, P. (2021). Hazardous infectious waste collection and government aid distribution during COVID-19: A robust mathematical leader-follower model approach. Sustainable Cities and Society, 69, 102814. https://doi.org/10.1016/j.scs.2021.102814
Valizadeh, J., & Mozafari, P. (2022). A novel cooperative model in the collection of infectious waste in COVID-19 pandemic. Journal of Modelling in Management, 17(1), 363–401. https://doi.org/10.1108/JM2-07-2020-0189
van Straten, B., Dankelman, J., van der Eijk, A., & Horeman, T. (2021). A Circular Healthcare Economy; a feasibility study to reduce surgical stainless steel waste. Sustainable Production and Consumption, 27, 169–175. https://doi.org/10.1016/j.spc.2020.10.030
WHO. (2021). World Health Organization. https://covid19.who.int/
Willis, H. H., Morral, A. R., Kelly, T. K., & Medby, J. J. (2006). Estimating Terrorism Risk. Rand Corporation.
Xin, L., Xi, C., Sagir, M., & Wenbo, Z. (2023). How can infectious medical waste be forecasted and transported during the COVID-19 pandemic? A hybrid two-stage method. Technological Forecasting and Social Change, 187, 122188. https://doi.org/10.1016/j.techfore.2022.122188
Yazdani, M., Tavana, M., Pamučar, D., & Chatterjee, P. (2020). A rough based multi-criteria evaluation method for healthcare waste disposal location decisions. Computers & Industrial Engineering, 143, 106394. https://doi.org/10.1016/j.cie.2020.106394
Yu, H., Sun, X., Solvang, W. D., Laporte, G., & Lee, C. K. M. (2020). A stochastic network design problem for hazardous waste management. Journal of Cleaner Production, 277, 123566. https://doi.org/10.1016/j.jclepro.2020.123566
Yu, H., Sun, X., Solvang, W. D., & Zhao, X. (2020). Reverse Logistics Network Design for Effective Management of Medical Waste in Epidemic Outbreaks: Insights from the Coronavirus Disease 2019 (COVID-19) Outbreak in Wuhan (China). International Journal of Environmental Research and Public Health, 17(5), 1770. https://doi.org/10.3390/ijerph17051770
Zografos, K. G., & Androutsopoulos, K. N. (2008). A decision support system for integrated hazardous materials routing and emergency response decisions. Transportation Research Part C: Emerging Technologies, 16(6), 684–703. https://doi.org/10.1016/j.trc.2008.01.004