Returns Acquisition Strategy in the Lot Sizing Problem with Refurbishing and Disassembly

The effective management of returns in the supply chain is crucial for maximizing profits and meeting the changing demands of customers. This study focuses on lot sizing in the context of reverse logistics, where returns vary in quality depending on the number and quality of their key parts. The study introduces an innovative approach that categorizes returned products by quality through key components. Companies assign purchase prices to different types of used products, refurbishing some to meet demand while disassembling others to extract key parts for production. A mathematical model is suggested to achieve maximum profit and meet customer demands for both new and used products. Using MINLP formulation, numerical tests evaluate how variations in return quality and quantity, as well as purchase price fluctuations, impact overall profitability across different scenarios. Results indicate the effectiveness of a dynamic pricing strategy for used products and highlight the benefits of a linear pricing approach. Sensitivity analysis underscores the importance of optimizing remanufacturing and refurbishment processes to maximize profits in reverse logistics settings.