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Computer Science > Computers and Society

arXiv:2301.09792 (cs)
[Submitted on 24 Jan 2023]

Title:Reverse Logistics Network Design to Estimate the Economic and Environmental Impacts of Take-back Legislation: A Case Study for E-waste Management System in Washington State

Authors:Hadi Moheb-Alizadeh, Amir Hossein Sadeghi, Amirreza Sahebi fakhrabad, Megan Kramer Jaunich, Eda Kemahlioglu-Ziya, Robert B Handfield
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Abstract:In recent years, recycling and disposal of end-of-life (EOL) electronic products has attracted considerable attention in response to concerns over resource recovery and environmental impacts of electronic waste (e-waste). In many countries, legislation to make manufacturers responsible for taking e-waste at the end of their useful lives either has been adopted or is being considered. In this paper, by capturing different stages in the life-cycle of EOL electronic products (or, e-waste) generated from private or small-entity users, we develop two different formulations of a reverse logistics network, i.e. system-optimum model and user-optimum model, to estimate both economic and environmental effects of take-back legislation. In this system, e-waste is collected through user drop-off at designated collection sites. While we study the whole reverse logistics network associated with recycling and remanufacturing of e-waste in the system-optimum model and obtain an optimum solution from the policy maker's perspective, we split the logistics network into two distinct parts in the user-optimum model in order to derive an optimum solution from the users' standpoint. Implementing the proposed models on an illustrative example shows how they are capable of estimating the economic and environmental impacts of take-back legislation in various stages of e-waste's life-cycle.
Comments: 42 pages, 7 figures, 11 tables
Subjects: Computers and Society (cs.CY); Optimization and Control (math.OC)
Cite as: arXiv:2301.09792 [cs.CY]
  (or arXiv:2301.09792v1 [cs.CY] for this version)
  https://doi.org/10.48550/arXiv.2301.09792

Submission history

From: Amir Hossein Sadeghi [view email]
[v1] Tue, 24 Jan 2023 02:50:09 UTC (2,996 KB)
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