Sustainable–resilient and climate-responsive e-waste supply chain network design under uncertainty using four-valued refined neutrosophic optimization

The rapid growth of electronic waste (e-waste) poses significant environmental and sustainability challenges and contributes to climate change. This paper presents a multi-objective, multi-period, mixed-integer linear programming (MILP) model of sustainable e-waste management, which incorporates economic, environmental, social, and risk-related objectives. The model focuses on maximizing four objectives, namely, (i) profit maximization, (ii) CO 2 emission reduction, (iii) maximization of job creation taking into account learning effects, and (iv) reduction of risk throughout the supply chain network. Moreover, the model addresses uncertainties in demand, recovery rates, and environmental conditions. The proposed model is solved using a four-valued refined neutrosophic optimization (FVRNO) approach, having a capability of dealing with truth, falsity, contradiction, and uncertainty in the decision-making process. A real-world e-waste case study validates the model. Computational results show that the proposed FVRNO approach is approximately 6.82 times and 11.82 times better than the epsilon-constraint and goal programming methods, respectively. The proposed framework supports circular economy implementation and climate-resilient decision-making for a sustainable e-waste management system aligned with the United Nations Sustainable Development Goals (SDGs).