Abstract
Minimizing the impact of electronic waste (e-waste) on the environment through designing an effective reverse supply chain (RSC) is attracting the attention of both industry and academia. To obtain this goal, this study strives to develop an e-waste RSC model where the input parameters are fuzzy and risk factors are considered. The problem is then solved through crisp transformation and decision-makers are given the right to choose solutions based on their satisfaction. The result shows that the proposed model provides a practical and satisfactory solution to compromise between the level of satisfaction of constraints and the objective value. This solution includes strategic and operational decisions such as the optimal locations of facilities (i.e., disassembly, repairing, recycling facilities) and the flow quantities in the RSC.
Highlights
The latest technological advances have considerably shortened the lifetime of electronic products
Obsolete or old electronics are rapidly being replaced by new models with more advanced functions and attractive designs [1]. This has led to electronic waste (e-waste) being one of the world’s fastest-growing wastes and it is estimated to increase to 52.2 million tonnes of e-waste in 2021 [2]
To diminish the significant impact of e-waste and recover valuable raw materials, a reverse supply chain (RSC) operation is considered as an effective approach [8,9]
Summary
The latest technological advances have considerably shortened the lifetime of electronic products. To diminish the significant impact of e-waste and recover valuable raw materials, a reverse supply chain (RSC) operation is considered as an effective approach [8,9]. Most input data (e.g., all costs involved, the capacity of centers, return rate, risk factors, etc.) in the proposed model are considered as fuzzy in nature, which can handle uncertain parameters in real situations. The proposed model aims to minimize the total cost including collection, set-up, processing, shipping, disposal, and risk costs as well as the profit obtained from selling recovery materials and used items. These facilities will serve to the end of the planning horizon In this RSC model, the returned products, cost parameters, the capacity of centers, and a fraction of components reused or recycled are major sources of uncertainties. This can support them to achieve the desired solution, while satisfying the company’s constraints
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