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There is a growing concern over environmental pollution resulting from the production. Moreover, the expansion of various industries has led to an increased demand for raw materials. To address these challenges, this paper aims to investigate the bi-objective optimization of a sustainable reverse supply chain network while considering two key sources of uncertainty in the returned product quality and the remanufacturing capacity. Additionally, the study considers the effects of carbon tax policies and government subsidies on remanufactured products, while also focusing on three important sustainability aspects - economic, social, and environmental. The study uses two quality thresholds at inspection centers to sort products, and the epsilon constraint and NSGA-II are applied to solve the model. Through numerical analysis, the research demonstrates that objective functions are sensitive to uncertain parameters and minimum acceptable quality levels. Furthermore, the study reveals that government subsidies can offset the negative effects of carbon tax policies.

journal of industrial and production engineering

A Bi-objective two-stage stochastic optimization model for sustainable reverse supply chain network design under carbon tax policy and government subsidy considering product quality