Evaluation of the flow of goods at a warehouse logistic department by Petri Nets

  • Carolina Gerini
  • Anna Sciomachen


This paper addresses the analysis issue of the complex interactions arising among different components of a warehouse logistic system. In particular, the focus is on a case study related to the handling operations required by the flow of goods within a store of Ikea, located in the center of Italy. The proposed study has been performed using Petri Nets (PNs) as discrete event modelling and simulation framework. In particular, this paper aims to bring out the innovative aspect of the use of PNs as tools to support the functional specifications of warehouse systems, highlighting their strengths and weakness. The goal is to emphasize critical factors in the entire logistic chain within the store and suggest solutions for improving its efficiency. In this regards, PNs have been proved to be quite suitable to easily represent the main features of the departments under consideration, showing at the same time the main logistic processes in which both labor and equipment are involved. The dynamics of the considered logistic system is evaluated, focusing on the three main operating cycles implemented at the Ikea store under consideration. Further, simulating directly the PN model, along with a quantitative analysis, has been possible to identify delays in the complete logistic chain and determine performance indices, such as utilization rate of the resources. Suggestions for improving the productivity of the system are given.


Petri Nets Warehouse and retail logistics Discrete event models Simulation Performance indices 


  1. Afshari H, Benam FH (2011) Retail logistics. In: Farahani R, Rezapour S, Kardar L (eds) Logistics operations and management. Concepts and models, 1st edn. pp 267–289CrossRefGoogle Scholar
  2. Anschuetz H (2003) HPSIM PN software tool.…/db/hpsim.html
  3. Arnold SJ (2002) Lessons learned from the world’s best retailers. Int J Retail Distrib Manag 30(11):562–570CrossRefGoogle Scholar
  4. Bartholdi JJ, Hackman ST (2014) Warehouse and distribution science. Georgia Institute of Technology, GeorgiaGoogle Scholar
  5. Bowersox DJ, Closs DJ, Bixby Cooper M (2002) Supply chain logistics management. In: First international edition. McGraw—Hill/Irwin, New YorkGoogle Scholar
  6. Cassandras CG, Lafortune S (2008) Introduction to discrete event systems, 2nd edn. Kluwer Academic, BostonCrossRefzbMATHGoogle Scholar
  7. Chiola G, Ajmone Marsan M, Balbo G, Conte G (1993) Generalized stochastic Petri Nets: a definition at the net level and its implications. IEEE Trans Softw Eng 19(2):89–107CrossRefGoogle Scholar
  8. Davidrajuh R, Lin B (2011) Exploring airport traffic capability using Petri Net based model. Expert Syst Appl 38:10923–10931CrossRefGoogle Scholar
  9. Dicesare F, Harhalakis G, Proth JM, Silva M, Vernadat FB (2012) Practice of Petri Nets in manufacturing. Springer, BerlinGoogle Scholar
  10. Dotoli M, Fanti MP, Mangini A, Stecco G, Ukovich W (2010) The impact of ICT on intermodal transportation systems: a modelling approach by Petri Nets. Control Eng Pract 18:893–903CrossRefGoogle Scholar
  11. Fukunar M, Malmborg CJ (2009) A network queuing approach for evaluation of performance measures in autonomous vehicle storage and retrieval systems. Eur J Oper Res 193:152–167CrossRefzbMATHGoogle Scholar
  12. Ghiani G, Laporte G, Musmanno R (2004) Introduction to logistics systems, planning and control. Wiley, New YorkGoogle Scholar
  13. Gil-Saura I, Servera-Frances D, Fuentes-Blasco M (2010) Antecedents and consequences of logistics value: and empirical investigation in the Spanish market. Ind Mark Manag 39(3):493–506CrossRefGoogle Scholar
  14. Girault C, Valk R (2001) Petri Nets for systems engineering: a guide to modeling, verification, and applications. Springer, New YorkzbMATHGoogle Scholar
  15. Giuia A, Silva M (2017) Modeling, analysis and control of discrete event systems: a Petri Net perspective. IFAC Papers OnLine 50–1:1772–1783CrossRefGoogle Scholar
  16. Hinrichs R (2015) Petri Nets and manufacturing systems, Clanrye InternationalGoogle Scholar
  17. Kabashkin I (2015) Modelling of regional transit multimodal transport accessibility with Petri Net simulation. Proc Comput Sci 77:151–157CrossRefGoogle Scholar
  18. Kuo PH, Krishnamurthy A, Malmborg CJ (2007) Design models for unit load storage and retrieval systems using autonomous vehicle technology and resource conserving storage and dwell point policies. Appl Math Model 31:2332–2346CrossRefzbMATHGoogle Scholar
  19. Lam HY, Choy LL, Ho GTS, Cheng SWY, Lee CKM (2015) A knowledge-based logistics operations planning system for mitigating risk in warehouse order fulfillment. Int J Prod Econ 170:763–779CrossRefGoogle Scholar
  20. Liu H, Wu W, Su H, Zhang Z (2016) Design of optimal Petri-Net controllers for a class of flexible manufacturing systems with key resources. Inf Sci 363:221–234CrossRefGoogle Scholar
  21. Ltifi M, Gharbi J (2015) The effect of logistics performance in retail store on the happiness and satisfaction of consumers. Proc Econ Financ 23:1347–1353CrossRefGoogle Scholar
  22. Malmborg CJ (2002) Conceptualizing tools for autonomous vehicle storage and retrieval systems. Int J Prod Res 40:1807–1822CrossRefzbMATHGoogle Scholar
  23. Marchet G, Melacini M, Perotti S, Tappia E (2012) Analytical model to estimate performance of autonomous vehicle storage and retrieval systems for product totes. Int J Prod Res 50:7134–7148CrossRefGoogle Scholar
  24. Messina E, Sciomachen A (1993) Evaluation of resource allocation policies in a production line using Petri Nets. Robot Comput Integr Manuf 10:413–422CrossRefGoogle Scholar
  25. Milinković S, Marković M, Vesković S, Ivić M, Pavlović N (2013) A fuzzy Petri Net model to estimate train delays. Simul Model Pract Theory 33:144–157CrossRefGoogle Scholar
  26. Negahban A, Smith JS (2014) Simulation for manufacturing system design and operation: literature review and analysis. J Manuf Syst 33:241–261CrossRefGoogle Scholar
  27. Peterson JL (1981) Petri Net theory and the modeling of systems. Prentice-Hall, New JerseyzbMATHGoogle Scholar
  28. Proth JM, Xie X (1997) Petri Nets: a tool for design and management of manufacturing systems. Wiley, HobokenGoogle Scholar
  29. Ramaswamy S, Valavanis KP, Barber S (1997) Petri Net extensions for the development of MIMO Net models of automated manufacturing systems. J Manuf Syst 16(3):176–191CrossRefGoogle Scholar
  30. Reisig W, Rozenberg G (1998) Lectures on Petri Nets I: basic models. advances in Petri Nets. In: Lecture in computer science, vol 1941, Springer, BerlinGoogle Scholar
  31. Rencko S, Ficko D (2010) New logistics technologies in improving customer value in retailing service. J Retail Consum Serv 17:216–223CrossRefGoogle Scholar
  32. Yue H, Xing K, Hu H, Wu W, Su H (2016) Petri net based robust supervisory control of automated manufacturing systems. Control Eng Pract 54:176–189CrossRefGoogle Scholar
  33. Zou B, Xu X, Gong YY, De Koster R (2016) Modelling parallel movement of lifts and vehicles in tier-captive vehicle-based warehousing systems. Eur J Oper Res 254:51–67CrossRefzbMATHGoogle Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Economics and Business StudiesUniversity of GenoaGenoaItaly

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