Abstract Electronic reverse logistics topic has received growing attention because of its environmental and economic impact. In Canada, the province of Ontario has enacted regulations regarding the Waste Electrical and Electronic Equipment (WEEE) Recycling program. The objective of this study is to develop a novel scenario-based robust possibilistic approach to optimize and configure an electronic reverse logistics network by considering the uncertainty associated with fixed and variable costs, the quantity of demand and return, and the quality of returned products. A Monte Carlo simulation is utilized to analyze the performance of our proposed model. Then, ANOVA test is conducted to statistically verify our model using the simulation results. The mathematical model is extended to the multi-objective optimization by maximising the environmental compliance of the third parties. The efficient solutions of the multi-objective model are computed using the two-phase fuzzy compromise approach. To provide a comprehensive assessment of the problem under investigation, we provide sensitivity analyses on the impact of different factors (e.g., recovery rates, capacity of facilities) on the total expected profit. Several interesting results were obtained, including the fact that increasing the capacity of facilities does not automatically translate into higher profits. Furthermore, by comparing the efficient solutions of deterministic and robust modes, we illustrate the impact of robustness price on the multi-objective model. The application of the proposed model is illustrated using a network in the Greater Toronto Area (GTA) in Canada.

中文翻译：

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基于场景的多目标电子逆向物流网络鲁棒可能性模型

摘要 电子逆向物流因其对环境和经济的影响而受到越来越多的关注。在加拿大，安大略省颁布了有关废弃电气和电子设备 (WEEE) 回收计划的法规。本研究的目的是开发一种新的基于场景的稳健可能性方法，通过考虑与固定和可变成本、需求和退货数量以及退货产品质量相关的不确定性来优化和配置电子逆向物流网络。蒙特卡罗模拟被用来分析我们提出的模型的性能。然后，进行方差分析测试以使用模拟结果统计验证我们的模型。通过最大化第三方的环境合规性，将数学模型扩展到多目标优化。使用两阶段模糊折衷方法计算多目标模型的有效解。为了对所调查的问题进行全面评估，我们对不同因素（例如，回收率、设施容量）对总预期利润的影响进行了敏感性分析。获得了几个有趣的结果，包括增加设施容量并不会自动转化为更高的利润这一事实。此外，通过比较确定性和稳健模式的有效解决方案，我们说明了稳健性价格对多目标模型的影响。