International Journal of Advances in Computer Science and Its Applications
Author(s) : LUKAS KOPECKI, SEBASTIAN LAUCK, SIMON BOXNICK
Sizing and redesign of new and existing supply chain nodes, like warehouses or logistic hubs are highly datadependent tasks, incorporating lots of transaction information which are mostly available through ERP systems. Therefore, item-based forecasting and lot sizing models, approximations or both are used widely when planning new supply chain nodes. This paper introduces a new approach of data-aggregation based on probability functions of each item (e.g. stock keeping units (SKU)) incorporating compensating behavior and timedependent aspects