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| URI | http://purl.tuc.gr/dl/dias/E04C0BBA-1050-4D94-83C9-FCE2C7AB8572 | - |
| Αναγνωριστικό | https://doi.org/10.1109/MED.2018.8442472 | - |
| Αναγνωριστικό | https://ieeexplore.ieee.org/document/8442472 | - |
| Γλώσσα | en | - |
| Μέγεθος | 6 pages | en |
| Τίτλος | Modeling task dependencies in project management using petri nets with Arc extensions | en |
| Δημιουργός | Tsinarakis Georgios | en |
| Δημιουργός | Τσιναρακης Γεωργιος | el |
| Εκδότης | Institute of Electrical and Electronics Engineers | en |
| Περίληψη | Alternative ways of modeling the four possible types of task dependencies in Project Management are introduced. The approach presented makes possible modeling and simulation of the execution procedure of complicated projects that can be analyzed in interconnected tasks, using Petri Nets and their extensions. The proposed method allows the calculation of the overall duration, as well as other useful measures according to the task durations and the interconnections between them. The advanced modeling power of Petri Nets makes possible the inclusion of random events (following a distribution or not) that in real world may disturb the project execution, as well as may change its duration and may lead to more accurate calculations compared to the traditionally used Project management tools and methods such as Network and Node diagrams. This can be used for more efficient project planning as well as for designing necessary actions to correct real time behavior of Project execution. | en |
| Τύπος | Πλήρης Δημοσίευση σε Συνέδριο | el |
| Τύπος | Conference Full Paper | en |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2019-06-07 | - |
| Ημερομηνία Δημοσίευσης | 2018 | - |
| Θεματική Κατηγορία | Petri nets | en |
| Θεματική Κατηγορία | Project Management | en |
| Θεματική Κατηγορία | Advanced modeling | en |
| Βιβλιογραφική Αναφορά | G. J. Tsinarakis, "Modeling task dependencies in project management using petri nets with Arc extensions," in 26th Mediterranean Conference on Control and Automation, 2018, pp. 84-89. doi: 10.1109/MED.2018.8442472 | en |
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