Online Recycling of Used Mobile Phones with Resilience Capability: A Stochastic Programming Approach with Benders Decomposition*

Online recycling has emerged as a promising solution for e-waste recovery by combining platform-based information matching with third-party delivery services. However, the effectiveness of this approach is hindered by inadequate supply chain management practices, resulting in challenges to achieving optimal sustainability and resilience. To address these challenges, this study designs a multi-period reverse logistics network that integrates consumers, operation centers, third-party logistics providers, and cascading processing facilities. A two-stage mixedinteger stochastic programming model is formulated to minimize costs and carbon emissions, fostering improvements in both sustainability and resilience. To solve this model efficiently, an advanced Benders decomposition algorithm is developed, incorporating acceleration techniques such as effective inequalities, induced constraints, and adaptive cuts. Comprehensive baseline and stress testing validate the algorithm's enhanced computational efficiency and robust performance.