Genetic-Based Approach for Minimum Initial Marking Estimation in Labeled Petri Nets
| Autor: | Lotfi Nabli, Achraf Jabeur Telmoudi, Hichem Kmimech, Layth Sliman |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Sequence General Computer Science Computer science Labeled Petri nets General Engineering Process (computing) label sequence 02 engineering and technology Petri net minimum initial marking Class (biology) genetic algorithms 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering optimization lcsh:TK1-9971 Algorithm |
| Zdroj: | IEEE Access, Vol 8, Pp 22854-22861 (2020) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2020.2967342 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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