An Efficient Scheduling Method in Supply Chain Logistics Based on Network Flow
Yichen Wang, H.L. Zhang, C. Z. Yuan, Xiangyu Li, Zuowen Jiang
Abstract
In the evolving digital landscape, network flow models have become integral to various sectors, including supply chain management. This research develops a robust network flow model for semiconductor wafer supply chains, optimizing resource allocation and addressing maximum flow challenges in production and logistics. The model incorporates the stochastic nature of wafer batch transfers and employs a dual-layer optimization framework to reduce variability and exceedance probabilities in finished goods. Empirical comparisons reveal significant enhancements in cost efficiency, productivity, and resource utilization, with a 20% reduction in time and production costs and a 10% increase in transportation and storage capacities. The model’s efficacy is underscored by a 15% decrease in transportation time and a 6700 kg increase in total capacity, demonstrating its capability to resolve logistical bottlenecks in semiconductor manufacturing. This study concludes that network flow models are a potent tool for optimizing supply chain logistics and offer a 23% improvement in resource utilization along with a 13% boost in accuracy. The findings provide valuable insights for supply chain logistics optimization.