Multi-objective two-stage stochastic optimization model for post-disaster waste management

• Autorzy: Boonmee Chawis , Legsakul Komkrit , Arimura Mikiharu

Identyfikatory

DOI

10.30657/pea.2023.29.8

• Języki publikacji: EN

Abstrakty

EN

Post-disaster waste management is one of the most crucial tasks in the recovery phase of the disaster cycle, and it was created to assist affected communities in returning to a stable state following a disaster. To develop an efficient post-disaster waste management strategy, this study presents a multi-objective two-stage stochastic mixed integer linear programming model for post-disaster waste management. The proposed mathematical model was developed based on a mixed strategy of on-site and off-site waste separation in the supply chain. This study aims to minimize not only the total cost and the environmental impact to provide waste flow decisions and choose collection and separation sites, recycling sites, landfill sites, and incineration sites throughout the supply chain under the uncertain situation. To solve a multi-objective problem, a normalized weighted sum method is used to find the solution. A numerical case based on realistic data is presented to validate and verify the proposed model. Based on the numerical example, the results demonstrated that the implementation of the mixed strategy for waste separation with the consideration of uncertain situations can reduce the total cost, balance the environmental impact, and determine the unexpected situation in the post-disaster waste supply chain efficiently.

Słowa kluczowe

EN

post-disaster; waste management; multi-objective; two-stage stochastic model

PL

po katastrofie; gospodarowanie odpadami; wielozadaniowość; dwustopniowy model stochastyczny

• Wydawca: Oficyna Wydawnicza Stowarzyszenia Menedżerów Jakości i Produkcji
• Czasopismo: Production Engineering Archives
• Rocznik: 2023
• Tom: Vol. 29, Iss. 1
• Strony: 58--68
• Opis fizyczny: Bibliogr. 15 poz., rys., tab.

Twórcy

autor

Boonmee Chawis

• Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai, Thailand

autor

Legsakul Komkrit

• Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai, Thailand

autor

Arimura Mikiharu

• Division of Sustainable and Environmental Engineering, Muroran Institute of Technology, Muroran, Japan

Bibliografia

• 1. Boonmee, C., Arimura, M., Asada, T., 2018. Location and allocation optimization for integrated decisions on post-disaster waste supply chain management: On-site and off-site separation for recyclable materials. International Journal of Disaster Risk Reduction, 31, 902-917, DOI: 10.1016/j.ijdrr.2018.07.003
• 2. Boonmee, C., Arimura, M., Kasemset, C., 2021. Post-disaster waste management with carbon tax policy consideration. Energy Reports, 7, 89-97, DOI: 10.1016/j.egyr.2021.05.077
• 3. Brown, C., Milke, M., 2016. Recycling disaster waste: Feasibility, method and effectiveness. Resources, Conservation and Recycling, 106, 21-32, DOI: 10.1016/j.resconrec.2015.10.021
• 4. Coppola, D.P., 2006. Introduction to international disaster management. Elsevier, Massachusetts, USA.
• 5. CRED, 2021 Disasters in numbers. Brussels, Available: https://www.un-spider.org. [Accessed: 15 July 2022].
• 6. Fetter, G., Rakes, T., 2012. Incorporating recycling into post-disaster debris disposal. Socio-Economic Planning Sciences, 46(1), 14-22, DOI: 10.1016/j.seps.2011.10.001
• 7. Habib, M.S., Sarkar, B., 2017. An integrated location-allocation model for temporary disaster debris management under an uncertain environment. Sustainability, 9(5), 716, DOI: 10.3390/su9050716
• 8. Habib, M.S., Sarkar, B., 2018. A multi-objective approach to sustainable disaster waste management. 2nd European International Conference on Industrial Engineering and Operations Management, Paris, France, 1072-1083.
• 9. Hu, Z.H., Sheu, J.B., 2013. Post-disaster debris reverse logistics management under psychological cost minimization. Transportation Research Part B: Methodological, 55, 118-141, DOI: 10.1016/j.trb.2013.05.010
• 10. Karunasena, G., Amaratunga, D., Haigh, R., Lill, I., 2009. Post disaster waste management strategies in developing countries: case of Sri Lanka. International Journal of Strategic Property Management, 13(2), 171-190, DOI: 10.3846/1648-715X.2009.13.171-190
• 11. Lorca, Á., Çelik, M., Ergun, Ö., Keskinocak, P., 2017. An optimization-based decision-support tool for post-disaster debris operations. Production and Operations Management, 26(6), 1076-1091, DOI: 10.1111/poms.12643
• 12. Manopiniwes, W., Irohara, T., 2017. Stochastic optimisation model for integrated decisions on relief supply chains: preparedness for disaster response. International Journal of Production Research, 55(4), 979-996, DOI: 10.1080/00207543.2016.1211340
• 13. Onan, K., Ülengin, F., Sennaroğlu, B., 2015. An evolutionary multi-objective optimization approach to disaster waste management: A case study of Istanbul. Turkey, Expert Systems with Applications, 42(22), 8850-8857, DOI: 10.1016/j.eswa.2015.07.039
• 14. Pramudita, A., Taniguchi, E., Qureshi, A.G., 2014. Location and routing problems of debris collection operation after disasters with realistic case study. Procedia-Social and Behavioral Sciences, 125, 445-458, DOI: 10.1016/j.sbspro.2014.01.1487
• 15. Wakabayashi, Y., Peii, T., Tabata, T., Saeki, T., 2017. Life cycle assessment and life cycle costs for pre-disaster waste management systems. Waste Management, 68, 688-700, DOI: 10.1016/j.wasman.2017.06.01428633912

Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).