国内动力电池即将迎来报废高峰期,但目前废旧动力电池回收网络尚未完善,对此有必要为其建立高效的逆向物流回收网络以提高回收效率和经济效益。此外存在许多缺乏专业回收能力的非正式组织,导致网络中废旧动力电池回收量具有不确定性。因此考虑各类动力电池回收量不确定性影响,以建设成本和运输成本最小为目标建立了逆向物流两阶段鲁棒优化模型。之后采用c&cg算法进行求解,通过随机规模算例结果验证了模型和方法有效性,为建立废旧动力电池回收网络提供了参考。The domestic power battery sector is approaching a peak in scrap disposal;however, the current recycling network for used batteries is not yet well-established. It is essential to create an efficient reverse logistics recycling network to enhance recovery efficiency and economic benefits. Additionally, many informal organizations lack specialized recycling capabilities, leading to uncertainty in the quantity of used power batteries recovered in the network. Therefore, considering the uncertainty in the recovery volume of various types of power batteries, a two-stage robust optimization model for reverse logistics has been developed, aiming to minimize construction and transportation costs. The c&cg algorithm was subsequently employed for solution, and results from randomly scaled examples validated the model and methodology, providing a reference for establishing a recycling network for used power batteries.
暂无评论