Abstract
Industrial systems are frequently characterized by processes where materials are processed in batches (finite discrete quantities) and many operations such as production, inventory replenishment, and distribution are usually performed in a way because of the nature of customer orders or in order to take advantages of the economies of scale. This brings in a need for new models which can describe and analyze the behaviors of these processes effectively. We recently introduced a new stochastic Petri net model called batch deterministic and stochastic Petri nets (BDSPNs) allowing the synchronization of discrete and token flows of the processes. In this work, the model is presented in a more formal way, its relevance to supply chain modeling is addressed, and its analysis methods are developed.
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