New approach combining numerical technique and simulation for analysis of large discrete event systems based on Petri nets

We propose a method that combines simulation and numerical techniques and directly integrated using interval arithmetic techniques for the analysis of large discrete event systems. A system is first divided into several layers. Identifying subsystems that can be modeled in isolation solves a system for each layer. In each subsystem, the Markovian assumption allows us to establish a set of linear equality constraints among the expectation of state variables in the Petri nets, such as token numbers in the places. A pseudo random process is responsible for the timing of the model, event times are completely determined by simulation. Thus, linear equality constraints are computed according to the pre-simulated event times, and it is possible to know the probabilities of interactions between subsystems.