A comparison of stochastic scheduling rules for maximizing project net present value

This paper examines the use of stochastic scheduling rules for maximizing the net present value of a project. A comprehensive set of 1440 test problems, representing five different project characteristics, is constructed. These test problems are used to evaluate the performance of nine stochastic scheduling rules. A simulated annealing scheduling procedure is shown to perform best, generating the highest net present values for most of the test problems. In certain environments, two previously examined rules, the Rank Positional Weight and a Discounted Cumulative Cash Flow Weight rule, also perform well with high net present values.