Time Petri nets (TPNs) have been widely used for modeling discrete event systems such as manufacturing, supply chain, and military systems. However, TPNs still have many drawbacks in some scenarios where an operation or process is associated with probability, and also lack appropriate simulation algorithms for analyzing different types of systems. In this paper, we address these two issues by proposing a class of extended time Petri nets (ETPNs) and presenting an appropriate simulation algorithm. We illustrate and validate our approach using a hypothetic command and control system, which shows that this approach could be a powerful tool for modeling and analyzing discrete event systems.
IdentifyTPN: a tool for the identification of Time Petri nets
