A generalized Monte Carlo simulation model for decision risk analysis illustrated with a Dutch elm disease control example

Abstract

Decision making is often performed under conditions of uncertainty and risk. A Monte Carlo simulation model is described which can help analyze alternatives where these conditions exist. The simulation model has a generalized format so that it may be easily applied to a number of different situations. The basic structure of the simulation model is discussed, and then the model is applied to a problem involving two Dutch elm disease (DED) control strategies. The simulation results, including probability density functions and cumulative distribution functions, are described.