Depth-First Net Unfoldings and Equivalent Reduction

Abstract

In Petri net unfolding, according to the strategies of breadth first and depth first, the biggest problem lies in the potential explosion of the state space. Unfolding generates either accessible trees or branch processes. Making marking reduction or branch cutting accessible proves to be an effective approach to mitigating the state space expansion. In this paper, we propose three reduction rules based on similarity equivalence, conduct state space reduction, present three theorems supported by a case study, and propose a new unfolding algorithm for the unfolding process. In both the new case and the experiments, the completeness, optimality, completeness, and memory and time consumption are reduced by about 60%.