Open AccessSUPPLY CHAIN RISK MANAGEMENT BY MONTE CARLO METHOD
Author(s) -
Tomasz Rymarczyk,
Grzegorz Kłosowski
Publication year - 2017
Publication title -
informatyka, automatyka, pomiary w gospodarce i ochronie środowiska
Language(s) - English
Resource type - Journals
eISSN - 2391-6761
pISSN - 2083-0157
DOI - 10.5604/01.3001.0010.7244
Subject(s) - monte carlo method , computer science , supply chain , fuzzy logic , valuation (finance) , artificial neural network , risk management , supply chain management , risk analysis (engineering) , artificial intelligence , economics , business , mathematics , statistics , finance , marketing , management
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.