Hybrid adaptive Petri nets: a conceptual framework for partial fluidization of Petri nets
Petri nets (PNs) constitute a well known family of formalisms for the modeling and analysis ofDiscrete Event Dynamic Systems (DEDS). As most formalisms for discrete event systems, PNssuffer from the state explosion problem, which renders enumerative analysis techniquesunfeasible for large systems. A technique to overcome the problem is to relax integralitycontraints of the discrete PN model, leading to continuous PN. This relaxation highly reducesthe complexity of analysis techniques but may not preserve important properties of theoriginal PN system such as deadlock‐freeness, liveness, reversibility, etc. This work focuses onHybrid Adaptive Petri nets (HAPNs), a Petri net based formalism in which the firing oftransitions is partially relaxed. The transitions of a HAPN can behave in two different modes:continuous mode for high transition workload, and discrete in other case. This way, a HAPN isable to adapt its behaviour to the net workload, it offers the possibility to represent morefaithfully the discrete model and use efficient analysis techniques by behaving as continuouswhen the load is high. Reachability space and the deadlock‐freeness property of hybridadaptive nets is studied in this work.