Abstract
This study focuses on the combined lot-sizing and scheduling challenge within a closed-loop supply chain that prioritizes sustainable production by incorporating returned products. The proposed system facilitates both the production of new items from raw materials and the remanufacturing of recovered goods using two parallel machines with limited capacity. These machines operate independently and manage operations with sequence-dependent setup times and costs. A mixed-integer programming (MIP) model is formulated to minimize total costs, which include production, remanufacturing, setup, inventory holding, backlog, and energy consumption. The model's performance is validated using a recognized benchmark instance from existing literature, highlighting its ability to produce efficient and cost-effective schedules.