Simulation study of inventory management in supply chains

Tomasz Wiśniewski


Well-organized management of the supply chain involves control of inventory levels and fast response to the changing customer demands. The enterprises can not cope with this problem which contributes to the growing stock levels and therefore increases costs. Thus, the main focus of this paper lies on the use of computer simulation techniques in order to emulate the supply chain system and its stochastic behaviour. The procedure for the usage of simulation modeling was described with a case study containing an analysis of online store. The simulation results are presented using statistical parameters, which means that the managers can get not only information concerning the expected value of the parameter looking decision-making, but also statistics to the characteristics of the risk associated with the decision associated with possible uncertainty.


supply chain; inventory management; computer simulation;

Full Text:



Beamon B. M., Chen V. C. P., Performance analysis of conjoined supply chains, "International Journal of Production Research", 39(2001)/14, pp. 3195-3218.

Chodak G., Latus L., Methods of Demand Forecasting and Inventory Management in Polish Internet Shops–Results of Research, 2011 -

Christiansen P. E., Kotzab H., Mikkola J. H., Coordination and sharing logistics in leagile supply chains, "International Journal of Procurement Management", 1(2007)/1-2, pp. 79–96.

Dooley F., Logistics, Inventory Control, and Supply Chain Management, "Choices: The magazine of food, farm and resource Issues", 20 2005)/4, pp. 1-5.

Duong L. N. K., Wood L. C., Wang W. Y. C., Research and Innovation in Manufacturing: Key Enabling Technologies for the Factories of the Future, [in:] Proceedings of the 48th CIRP Conference on Manufacturing Systems, Procedia Manufacturing, 2015, pp. 266–276.

Fisher M., What is the right supply chain for your product?, "Harvard Business Review", (1997), pp. 105-116.

Holweg M. D. S., Holmström J., Smäaros J., Supply chain collaboration: Making sense of the strategy continuum, "European Management Journal", 23(2005)/2, pp. 170-181.

Jammernegg W., Reiner G., Performance improvement of supply chain processes by coordinated inventory and capacity management, "International Journal of Production Economics, 108(2007), pp. 183–190.

Jung I. Y., Blau G., Pekny J., Gintaras F., Reklaitis V., Eversdyk D., (2004), A simulation based optimization approach to supply chain management under demand uncertainty, Computers and Chemical Engineering, 28(2004)/10, pp. 2087–2106.

Kristianto N. Y., Production ramp up in built-to-order supplier chain, "Journal of Modelling in Management", 6(2011)/2, pp. 143-163.

Liu J., Hou Y. R., Time based strategy in distribution logistics: gaining competitive advantages in IKEA, Bachelor‟s Thesis in Industrial Management & Logistics, 2011.

Narmadha S., Selladurai V., Multi-factory, Multi-Product Inventory Optimization using Genetic Algorithm for Efficient Supply Chain Management, "JCSNS International Journal of Computer Science and Network Security", 9(2009)/12, pp. 203-212.

Park Y.-B., Kim H. S., Simulation-based evolutionary algorithm approach for deriving the operational planning of global supply chains from the systematic risk management, "Computers in Industry", 83(2016), pp. 68–77.

Scheuffele G., Kulshreshta A., Inventory Optimization: A Necessity Turning to Urgency, "SETLabs Briefings", 5 (2007)/3, pp. 15-24.

Schmitt A. J., Singh M., A quantitative analysis of disruption risk in a multi- echelon Supply chain, "International Journal of Production Economics", 139(2012)/1, pp. 22–32.

Torkul O., Yılmaz R., Selvi I. H., Cesur M. R., A real-time inventory model to manage variance of demand for decreasing inventory holding cost, "Computers and Industrial Engineering", 102 (2016), pp. 435–439.

Thierry C., Narahari Y., Thomas A., The role of modelling and simulation in supply chain management, “SCS M&S Magazine”, 1(2010)/4, pp. 1-8.


  • There are currently no refbacks.