A new environment-aware scheduling method for remanufacturing system with non-dedicated reprocessing lines using improved flower pollination algorithm. (October 2020) - Shi, Jiaxuan; Zhang, Wenyu; Zhang, Shuai; Wang, Weirui; Lin, Jian; Feng, Ruijun
Highlights: A new environment-aware scheduling model for remanufacturing system is proposed. Three subsystems of remanufacturing system and non-dedicated reprocessing lines are integrated in the proposed model. The carbon emissions of machines are considered to take advantage of the environmental benefits in remanufacturing. An improved flower pollination algorithm is presented to solve the proposed model. Experiments are performed to demonstrate the effectiveness of the proposed algorithm. Abstract: As the resource crisis and environmental pollution become increasingly prominent, remanufacturing is currently a popular research field for addressing these issues. However, scheduling for remanufacturing is more difficult than that for traditional manufacturing because the entire remanufacturing system (RMS) involves three cooperative subsystems: disassembly, reprocessing, and reassembly. Few studies have focused on the scheduling of the entire RMS and addressed the quality differences of defective components using non-dedicated reprocessing lines. Thus, this paper proposes a new environment-aware scheduling model for RMS, which considers not only three subsystems simultaneously, but also the non-dedicated reprocessing lines related to the recycled quality of defective components. The proposed model also integrates environmental factors by considering the carbon emissions of machines to take advantage of the environmental benefits in remanufacturing. To solve the proposed model, an improved flower pollination algorithm with new two-dimensional representation scheme is employed, which not only utilizes the self-adaptive parameter but also integrates path relinking technique, local search strategy, and elite replacement strategy. Experiments are performed to illustrate the effectiveness of the proposed algorithm for solving the remanufacturing scheduling problem by comparing it with six baseline algorithms.