SUPPLY CHAIN RISK MANAGEMENT BY MONTE CARLO METHOD

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DOI

Tomasz Rymarczyk

tomasz@rymarczyk.com

Grzegorz Kłosowski

g.klosowski@pollub.pl

Abstract

In this paper, the conceptual model of risk-based cost estimation for completing tasks within supply chain is presented. This model is a hybrid. Its main unit is based on Monte Carlo Simulation (MCS). Due to the fact that the important and difficult to evaluate input information is vector of risk-occur probabilities the use of artificial intelligence method was proposed. The model assumes the use of fuzzy logic or artificial neural networks – depending on the availability of historical data. The presented model could provide support to managers in making valuation decisions regarding various tasks in supply chain management.

Keywords:

project management, decision support systems, neural networks, fuzzy logic

References

Article Details

Rymarczyk, T. ., & Kłosowski, G. . (2017). SUPPLY CHAIN RISK MANAGEMENT BY MONTE CARLO METHOD. Informatyka, Automatyka, Pomiary W Gospodarce I Ochronie Środowiska, 7(4), 20–23. https://doi.org/10.5604/01.3001.0010.7244