Modeling Supply Chains Using Colored Petri Nets: Application in A Phosphate Supply Chain


Azougagh Yassine,Benhida Khalid,Elfezazi Said,



Supply chain,Modelling,Colored Petri nets,Phosphate industry,


To evaluate the performance and dynamic of a supply chain and to better understand its behavior, it is necessary to start a modeling process. For this purpose, various tools and approaches are used. Among these tools, we can use the Petri nets. With this background, the scientific literature mentions some studies using Petri nets for modeling and performance analyzing of industrial systems such as production, procurement, distribution systems... However, taking into consideration all aspects of supply chain, there were a few studies focusing on this kind of tools in supply chains modelling. The aim of this investigation was to complement the existing works, by applying the Petri nets tool, specifically colored Petri nets, for modeling a real phosphate supply chain.


I. Ajmone Marsan M., Balbo G., Conte G., Donatelli, S., and Franceschinis G.
(1995). Modelling with Generalized Stochastic Petri Nets. John Wiley and
II. Alla. H. (1987). Réseaux de Petri colorés et réseaux de Petri continus :
application à l’étude des systèmes à événements discrets”, PhD Thesis,
University of Grenoble, France, Jun.
III. Arns M, Fischer M, Kemper P, and Tepper C. (2002). Supply chain modeling
and its analytical evaluation. Journal of Operational Research Society, 53:
IV. Baldwin L. P., Eldabi T., Paul R. J. (2004). Simulation in healthcare
management: a soft approach. Simulation Modelling Practice and Theory, 12:
V. Beamon M. (1998). Supply chain design and analysis: models and method.
International Journal of Production Economics, 55: 281-294.
VI. Cassandras C.G. (1993). Discrete event systems: modeling and performances
analysis, Aksen Ass. Inc. Pub.
VII. Chen H., Amodeo L., Chu F., and Labadi K. (2005). Performance Evaluation
and Optimization of Supply Chains modelled by Batch Deterministic and
Stochastic Petri. IEEE transactions on Automation Science and Engineering,
VIII. Chen Y., Peng Y., Finin T., Labrou Y., Cost S., Chu B., Yao J., Sun R, and
Wilhelm B. (1999). A negotiation-based multi-agent system for supply chain
management. Proceedings of the Agents Workshop.
IX. Dong M., and Chen F.F. (2001). Process modeling and analysis of
manufacturing supply chain networks using object-oriented Petri nets.
Robotics and Computer Integrated Manufacturing, 17 (1-2):121-129.

X. Dragana Makajić-Nikolić, Biljana Panić, Mirko Vujošević. (2004). Bullwhip
Effect and Supply Chain Modelling and Analysis Using CPN Tools. Fifth
Workshop and Tutorial on Practical Use of Colored Petri Nets and the CPN
Tools, Aarhus, Denmark, 8(11):219-234.
XI. Farideh Haghshenas Kashani, Mahsa Soleimani. (2015). Evaluation of
investment resources impact on development of formal education
management system. International Journal of Advanced and Applied
Sciences, 2(10) : 52‐61.
XII. Florin G. (1985). Réseaux de Petri stochastiques, théorie et techniques de
calcul. PhD Thesis, University of Pierre and Marie Curie, Paris VI.
XIII. Ganeshan R., Jack E., Magazine M.J., Stephens P. (1998). A Taxonomic
Review of Supply Chain Management Research, in Quantitative Models for
Supply Chain Management. Kluwer Academic Publishers: 841-880.
XIV. Gunasekaran, A., and Kobu, B. (2007). Performance measurements and
metrics in logistics and supply chain management: a review of recent
literature for research and applications. International Journal of Production
Research, 45: 2819-2840.
XV. Haas P. J. (2002). Stochastic Petri Nets: Modeling, Stability, Simulation.
Springer Verlag, New York.
XVI. Harrel C., Tumay K. (1994). Simulation made easy, Engineering &
Management Press.
XVII. Jensen, Kurt. (1996). Coloured Petri Nets. Berlin: Heidelberg, (2): 234.
XVIII. Kleijnen J.P.C. (2005). Supply chain simulation tools and techniques: a
survey. International Journal of Simulation & Process Modelling, (1) : 82-89.
XIX. Labadi K. (2005). Contribution à la modélisation et l’analyse des chaines
logistique à l’aide des réseaux de Petri. PhD Thesis, University of Technology
of Troyes .
XX. Labarthe O. (2006). Modélisation et simulation orientées agents de chaînes
logistiques dans un contexte de personnalisation de masse : modèles et cadre
méthodologique, PhD Thesis, University of Laval Québec and University of
Paul Cézanne Marseille : 30-100.
XXI. Landeghem R.V., Bobeanu C. V. (2002). Formal modelling of Supply Chain:
An Incremental Approach Using Petri Nets. Proceedings 14th European
Simulation Symposium A. Verbraeck, W Krug, eds. (c) SCS Europe BVBA.
XXII. Law A. M., McComas M. G. (2001). How to build valid and credible
simulation models, Proceedings of the Winter Simulation Conference: 22-29.
XXIII. Lefebvre, D. and P. Thomas. (2005). Parameters estimation for timed and
continuous Petri nets: application to the identification and monitoring of
hybrid systems. Cybernetics and Systems, 36(3): 217-250.
XXIV. Lindemann C. (1998). Performance Modelling with Deterministic and
Stochastic Petri Nets. John Wiley and Sons.

XXV. Mevius M. V., Pibernik. R. (2004). Process Management in Supply Chains-
A New Petri-Net based Approach. Proceedings of the 37th Annual Hawaii
International Conference on System Sciences, Hawaii: 05-08.
XXVI. Min H., Zhou G. (2002). Supply chain modelling: past, present and future.
Computers & Industrial Engineering, 43: 231-249.
XXVII. Reisig, W. (1985). Petri Nets: An introduction. Springer-Verlag.
XXVIII. Smata N., Tolba C., Boudebous D., Benmansour S., Boukachour J. (2011).
Modélisation de la chaîne logistique en utilisant les réseaux de Pétri continus.
Proceeding of the 9th International conference in Industrial engineering,
XXIX. Su S., Shih C.L. (2003). Modeling an emergency medical services system
using computer simulation. International Journal of Modeling Information.
72: 57-72.
XXX. Swati Hira, Anita Bai, P. S. Deshpande. (2016). Designing multidimensional
model using relational schema. International Journal of Advanced and
Applied Sciences, 3(5): 1‐8.
XXXI. Tan Ching NG, Morteza Ghobakhloo. (2017). What derives lean
manufacturing effectiveness: An interpretive structural model. International
Journal of Advanced and Applied Sciences, 4(8): 104-111.
XXXII. Trilling L., Besombes B., Chaabane S., Guinet A. (2004). Modélisation des
pratiques : Investigation et Comparaison des Méthodes et Outils d’Analyses
pour l’Etude des Systèmes Hospitaliers, HRP project report, Academic Press.
XXXIII. Van der Vorst, Jack G.A.J., Beulens J.M, van Beek P. (2000). Modelling and
simulating Multi-echelon Food Systems. European Journal of Operational
Research, 122: 354-366.
XXXIV. Viswanadham N., Srinivasa Raghavan N. R. (2000). Performance Analysis
and Design of Supply Chains: A Petri Net Approach. Journal of the
Operational Research Society, 51(10): 1158-1169.
XXXV. Wang Jiacun. (1998). Timed Petri Nets: Theory and Application. Kluwer
Academic Publishers.
XXXVI. Zaytoon J. (1998). Hybrid dynamical systems, APII – JESA, 32: 9-10.
XXXVII. Zhou Mengchu and Kurapati Venkatesh. (1999). Modeling, Simulation, and
Control of Flexible Manufacturing Systems: A Petri Net Approach. vol 6 of
Series in Intelligent Control and Intelligent Automation. World Scientific.

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