inis 16(8): e3

Research Article

TiPeNeSS: A Timed Petri Net Simulator Software with Generally Distributed Firing Delays

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  • @ARTICLE{10.4108/eai.24-8-2015.2261343,
        author={\^{A}d\^{a}m Horv\^{a}th and Andr\^{a}s Moln\^{a}r},
        title={TiPeNeSS: A Timed Petri Net Simulator Software with Generally Distributed Firing Delays},
        journal={EAI Endorsed Transactions on Industrial Networks and Intelligent Systems},
        volume={3},
        number={8},
        publisher={ACM},
        journal_a={INIS},
        year={2015},
        month={8},
        keywords={simulation, timed petri net, general distribution},
        doi={10.4108/eai.24-8-2015.2261343}
    }
    
  • Ádám Horváth
    András Molnár
    Year: 2015
    TiPeNeSS: A Timed Petri Net Simulator Software with Generally Distributed Firing Delays
    INIS
    EAI
    DOI: 10.4108/eai.24-8-2015.2261343
Ádám Horváth1,*, András Molnár1
  • 1: Institute of Informatics and Economics, University of West Hungary
*Contact email: horvath@inf.nyme.hu

Abstract

Performance analysis can be carried out in several ways, especially in case of Markovian models. In order to interpret high level of abstraction, we often use modeling tools like timed Petri nets (TPNs). Although some subclasses of TPNs (e.g. stochastic Petri nets (SPNs) [17, 19]) can be handled analytically, a general timed Petri net is hard to evaluate via numerical analysis. However, the simulation of SPNs or deterministic and stochastic Petri nets (DSPNs) [16] are supported by many known tools (see, e.g. [3, 20]), it is hard to find a simulation tool for timed Petri nets with generally distributed (i.e., particular but arbitrarily chosen) firing times. In this paper, we present TiPeNeSS (Timed Petri Net Simulator Software) which supports the simulation of timed Petri nets containing transitions with generally distributed firing delays. The input of the software (the Petri net and the parameters) is defined in an XML file, what allows us to generate results in batch mode. Besides, we describe a case study in which we optimize the frequency of the regular maintenance in a manufacturing process.