SUPPLY CHAIN RISK MANAGEMENT BY MONTE CARLO METHOD - Rymarczyk, Tomasz; Kłosowski, Grzegorz (Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska, 2017)
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.