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Genetic-Based Approach for Minimum Initial Marking Estimation in Labeled Petri Nets

Article scientifique 2020 Anglais

Résumé

Computing the minimum initial marking (MIM) in labeled Petri nets (PN) while considering a sequence of labels constitutes a difficult problem. The existing solutions of such a problem suffer from diverse limitations. In this paper, we proposed a new approach to automatically compute the MIM in labeled PNs in a timely fashion. We adopted a genetic-based algorithm to model the MIM problem. The choice of such an algorithm is justified by the nature of the MIM process which belongs to the NP-hard class. We experimentally showed the effectiveness of our approach and empirically studied the initial marking quality in particular.

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Hichem, K., Telmoudi, A., Sliman, L., Nabli, L. (2020). Genetic-Based Approach for Minimum Initial Marking Estimation in Labeled Petri Nets. https://doi.org/10.1109/access.2020.2967342

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Auteur(s)

Kmimech Hichem Achraf Jabeur Telmoudi Layth Sliman Lotfi Nabli

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