Abstract Waste generation across various categories such as municipal waste, industrial byproducts, medical discards continues to grow in both quantity and complexity due to population growth, urbanization, and advancements in technology. Improper waste management (WM), driven by human activities, is a major contributor to environmental pollution, making effective waste handling a critical priority for all nations. This study focuses on managing waste by minimizing total transportation cost, restricting carbon emission, and mitigating impacts on public health through a multi-objective optimization (MOO) framework. To address uncertainties in supply and demand fluctuations, the model incorporates type-2 intuitionistic fuzzy sets. Global criterion method (GCM) is applied to obtain Pareto-optimal solutions that balance multiple conflicting objectives. To validate the practicality of the proposed approach, a real-world case study based on Addis Ababa, Ethiopia, is presented, alongside several generated benchmark instances. Furthermore, the performance of GCM is compared with two existing MOO techniques to demonstrate its effectiveness in generating solutions. The study also includes a comparative analysis, sensitivity analysis, and managerial insights to support decision-making.
Bera et al. (Tue,) studied this question.