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<p>The enhancement of cyclic Petri nets (PN) identified from a set S of event sequences generated by discrete event processes is addressed. The refinement aims to yield a model that accurately describes the sequencing of job execution and represents a low surplus language. A novel method that extends discovery methods for concurrent repetitive processes dealing with long sequences of events that include all variants process behaviour, is presented. Given a PN <i>N</i> and its set of minimal t-invariants Y, the method analyses the execution of the t-components in every sequence in S; it determines patterns of representative transitions S<sub>Y</sub> that schedule the execution of t-components in <i>N</i>. Afterwards, S<sub>Yi</sub> are treated to identify a new PN <i>N</i>’ that uses S<sub>Y</sub> and new places; <i>N</i>’ schedules the occurrence of representative transitions in <i>N</i>. The enhanced model <i>N</i>’’ is obtained by merging the representative transitions of both <i>N</i> and <i>N</i>’.</p>

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Enhancement of Petri nets identified from discrete-event processes by scheduling t-components

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月14日

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  • Ernesto López-Mellado,
  • Yolanda Álvarez-Pérez

摘要

The enhancement of cyclic Petri nets (PN) identified from a set S of event sequences generated by discrete event processes is addressed. The refinement aims to yield a model that accurately describes the sequencing of job execution and represents a low surplus language. A novel method that extends discovery methods for concurrent repetitive processes dealing with long sequences of events that include all variants process behaviour, is presented. Given a PN N and its set of minimal t-invariants Y, the method analyses the execution of the t-components in every sequence in S; it determines patterns of representative transitions SY that schedule the execution of t-components in N. Afterwards, SYi are treated to identify a new PN N’ that uses SY and new places; N’ schedules the occurrence of representative transitions in N. The enhanced model N’’ is obtained by merging the representative transitions of both N and N’.