A multi-objective integrated scheduling of remanufacturing system considering time window constrained outsourcing option

The current strategy of collaborative production is garnering attention in the remanufacturing industry. The collaborative execution of tasks through the sharing of production resources such as facilities and labor can effectively augment the utilization rate of end-of-life products. However, existing studies on scheduling problem in remanufacturing systems does not take into this issue. To fill this gap, this study considers an integrated scheduling problem in remanufacturing systems with parallel disassembly workstations, a flexible-shop-type reprocessing shop and a reassembly workstation, where the components obtained by disassembling can be outsourced within the time window given by the outsourcer. To address this issue, a mathematical model aiming at minimizing the completion time and total cost is established. Then, a knowledge guided artificial bee colony algorithm (KGABC) with a five-layer encoding scheme is proposed to solve it. In the KGABC, a two-step heuristic initialization approach is invented based on the characteristics of the disassembly and reprocessing stage. According to the problem-specific knowledge, a reprocessing advance scheduling approach is proposed to reduce idle time; an outsourcing assessment method is presented for determining the feasibility of outsourcing operation; a reassembly priority management strategy is put forward to determine the reassembly sequence of products. In addition, a knowledge guided search strategy is proposed in the onlooker bee phase to enhance the local search ability of the algorithm. Finally, the KGABC is subjected to comparative testing against the state-of-the-art algorithms on numerical benchmark instances with different scales. Simulation results show that the KGABC exhibits significant advantages in terms of solution accuracy, solution diversity, and convergence properties. Moreover, a real case study is adopted to validate KGABC's supremacy in solving the real-world remanufacturing scheduling problem with relatively lower time and cost.