Reverse Logistics Network Design for Infected Medical Waste Management in Epidemic Outbreaks under Uncertainty: A Case Study of COVID-19 in Pathum Thani, Thailand

Main Article Content

Pornpawee Supsermpol
Sun Olapiriyakul
Navee Chiadamrong


Disease outbreaks cause disruption in the economy and threaten human life. This study proposes a Fuzzy Multi-Objective Multi- Period Mixed-Integer Linear Programming (FMOMILP) model for effective IMW
management in outbreaks under uncertain environments considering financial and risk aspects. The strategic decision is to determine
optimal locations and suitable capacity levels of temporary facilities, including temporary storage centers and temporary treatment centers, as wellas optimal transportation strategies. To solve the proposed FMOMILP model, an integrated interactive fuzzy approach is employed. First, an equivalent auxiliary crisp model is used to handle the uncertainties by the feasibility degree (α) concept. The problem is solved using Fuzzy Goal Programming (FGP). A case study of the COVID-19 outbreak in Pathum Thani province in Thailand was carried out to demonstrate the proposed model’s performance. The proposed method yields solutions with varying feasibility degrees and allowed percentage deviations, providing alternatives for the decision-makers. The contribution of this study helps identify the optimal setting of temporary facilities in appropriate locations and seizes and improves the performance of IMW management subject
to the uncertainty of data by trading off between conflicting objectives. A comparison of the results with (optimal solution) and without (actual
solution) temporary facilities is also presented.

Article Details

How to Cite
Supsermpol, P. ., Olapiriyakul , S. ., & Chiadamrong, N. (2022). Reverse Logistics Network Design for Infected Medical Waste Management in Epidemic Outbreaks under Uncertainty: A Case Study of COVID-19 in Pathum Thani, Thailand. INTERNATIONAL SCIENTIFIC JOURNAL OF ENGINEERING AND TECHNOLOGY (ISJET), 6(2), 66–82. Retrieved from
Research Article


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