Hierarchical supply chain planning using artificial neural networks to anticipate base-level outcomes

Abstract.

Most Advanced Planning Systems decompose the task of production planning according to the planning horizon in two levels, mid-term and short-term planning. The mid-term planning level sets the targets for the short-term level. In response, the short-term planning level gives feedback to the mid-term level. Moreover, due to detailed knowledge, the short-term planning level should provide relevant input to the mid-term planning run. To compute accurate targets for the short-term planning level the mid-term planning should anticipate its major behaviour. In this article we present an artificial neural network based anticipation of a short-term planning level for a single-stage, multi-product flow line production environment.