SUPPLY CHAIN RISK MANAGEMENT BY MONTE CARLO METHOD
Tomasz Rymarczyk
tomasz@rymarczyk.comResearch and Development Center, Netrix S.A., Lublin; University of Economics and Innovation in Lublin, (Poland)
Grzegorz Kłosowski
Lublin University of Technology, Faculty of Management, Department of Organization of Enterprise (Poland)
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 logicReferences
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Authors
Tomasz Rymarczyktomasz@rymarczyk.com
Research and Development Center, Netrix S.A., Lublin; University of Economics and Innovation in Lublin, Poland
Authors
Grzegorz KłosowskiLublin University of Technology, Faculty of Management, Department of Organization of Enterprise Poland
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