Performance evaluation of logistics with componentized stochastic models

This work proposes the use of pre-defined generalized stochastic Petri net (GSPN) components to model and evaluate outbound logistics. The modeling process takes into account the automatic generation of these stochastic models from high-level end-user-oriented descriptions. The model resultant from this translation is guaranteed to have some expected Petri nets´ properties. The Stochastic Logistics Optimizer Tool (SLOT) was implemented with the aim of supporting the modeling process based on a component library. Case studies were carried out and one of them is presented.