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.