A Network Flow Approach to Optimal Scheduling in Supply Chain Logistics

TL;DR

This paper introduces a network flow model tailored for semiconductor supply chains, significantly improving efficiency and capacity while reducing costs and transit times through advanced optimization techniques.

Contribution

It develops a dual-layer network flow model that accounts for stochastic batch transfers, enhancing supply chain performance in semiconductor manufacturing.

Findings

20% reduction in time and production costs

10% increase in transportation and storage capacities

15% decrease in transportation time

Abstract

In the evolving digital landscape, network flow models have transcended traditional applications to become integral in diverse 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, offering a 23% improvement in resource utilization and a 13% boost in accuracy. The findings provide valuable insights for supply chain logistics optimization.