Reverse logistics network design with a 3-phase interactive intuitionistic fuzzy goal programming approach: a case study of COVID-19 in Pathum Thani, Thailand

During outbreaks, a vast quantity of Infected Medical Waste (IMW) can be substantially generated in a short period of time. Without proper management, the IMW rapidly accumulates and poses a huge risk to medical personnel and surrounding communities. Thus, an effective IMW reverse logistics network design plays an essential role in controlling the spreading of disease. This study proposes an Intuitionistic Fuzzy Multi-Objective Multi-Period Mixed-Integer Linear Programming (IFMOMILP) model for an effective IMW management in outbreaks under uncertainty, taking into account financial and risk factors subject to a priority from Decision Makers (DMs). The primary emphasis is on determining the best optimal locations and capacity levels for temporary facilities, which include temporary storage and treatment centers, as well as the optimal transportation routes. A 3-phase interactive Intuitionistic Fuzzy Goal Programming (i-IFGP) approach is developed to solve this IFMOMILP model. First, Jiménez approach is applied to handle the uncertainties. Then, the problem is solved by Intuitionistic Fuzzy Goal Programming (IFGP) and a comparison between the fuzzy goal programming and the intuition fuzzy goal programming under an optimal solution computation is done to present the best outcome subject to uncertainty in information and hesitation in a decision-making process. A real case study of the COVID-19 outbreak in Pathum Thani province in Thailand was carried out to demonstrate the effectiveness of the proposed approach. The proposed approach yields solutions with varying feasibility degrees and scaling factors, providing alternatives for DMs. It also provides the details about the acceptable degree (µ), rejective degree (ν), and the hesitation index (π) of the outcomes, and the score function is utilized to imply DMs’ satisfactory with the outcomes, which is a concrete measure since it can reflect the intention of the DMs.