An Integrated Approach to Stochastic Decisionmaking: A Project Scheduling Example

Several classical approaches in decisionmaking are integrated to analyze a stochastic decisionmaking problem. The techniques include Monte Carlo simulation, linear programming, and decision theory. The problem being analyzed is the project scheduling for the construction of a highway. Through this integrated approach the uncertainties with respect to the project´s cost versus the project´s execution are quantified. Specifically, an empirical probability density function for the optimal solution is generated. Subsequent analysis depicts the trade-offs facing the decisionmaker. Through this analysis the efficacy of decisionmaking approaches based upon mathematical programming versus decision theory are contrasted for this example.