Statistical Input Data Analysis for Supply Chain Simulation

Abstract

Statistical Input Data Analysis for Supply Chain Simulation Stochastic simulation models utilize probability distributions to represent a multitude of randomly occurring events. Theoretical distributions are used to represent empirical data because they help smooth data irregularities that may exist due to values missed during the data collection period. The incompatibility between specific characteristics of the theoretical distribution and assumptions of simulation and mathematical calculus present an actual problem in supply chains. The paper is based on the analysis of mentioned contradictions. Different approaches to deal with theoretical probability distributions in supply chains are described in the paper.