Structural Methods to Improve the Symbolic Analysis of Petri Nets

Abstract. Symbolic techniques based on BDDs (Binary Decision Diagrams) have emerged as an e cient strategy for the analysis of Petri nets. The existing techniques for the symbolic encoding of each marking use a xed set of variables per place, leading to encoding schemes with very low density. This drawback has been previously mitigated by using Zero-Suppressed BDDs, that provide a typical reduction of BDD sizes by a factor of two. Structural Petri net theory provides P-invariants that help to derive more e cient encoding schemes for the BDD representations of markings. P-invariants also provide a mechanism to identify conservative upper bounds for the reachable markings. The unreachable markings determined by the upper bound can be used to alleviate both the calculation of the exact reachability set and the scrutiny of properties. Suchapproach allows to drastically decrease the number of variables for marking encoding and reduce memory and CPU requirements signi cantly.

• Type: Conference
• Year: 1999
• Where: APN
• Authors: Enric Pastor, Jordi Cortadella, Marco A. Peña
• Keywords: APN 1999, Artificial Intelligence, Cient Encoding Schemes, Petri Net, Symbolic Encoding