Application des BDSPNs à la modélisation et à l'évaluation de performances des chaînes logistiques

Abstract

Batch deterministic and stochastic Petri nets (BDSPNs) are a class of Petri nets developed for modelling, analysis and performance evaluation of supply chains and more generally stochastic discrete event systems with batch behaviour. BDSPNs extends DSPNs by introducing batch places and batch tokens, which permit it to efficiently model batch behaviours of batch discrete event processes appeared often in production systems, inventory systems, and supply chains. In those systems, materials are processed in batches (finite discrete quantities) and many operations such as inventory replenishment, manufacturing and distribution operations are usually performed in batch mode to take advantages of the economies of scale or because of the batch nature of customer orders. In this paper, the model and its dynamical behaviour are defined formally. Methods for analysis and evaluation of the performance of the model are then developed. As applications, the performances of an inventory system and of a supply chain are evaluated analytically and by simulation, respectively, by using the BDSPN modelling and analysis tool. The applications demonstrate the advantages of BDSPNs as a tool for modelling, analysis and performance evaluation of supply chains.