Simulation-based priority rules for the stochastic resource-constrained net present value and risk problem

In this paper, the performance of activity-based and resource-based policies with newly designed priority rules for stochastic resource-constrained project scheduling problem is considered. The aim paper to maximize expected net present value (eNPV) minimize risk project's by semivariance measurement. 16 (mainly cash flow-based) heuristic are considered, among which 10 derived from deterministic NPV literature referred as direct rules, 6 developed based on simulation information. these in mentioned objective functions has been evaluated benchmark data set library. have ranked separately maximization eNPV minimization semivariance. computational results various test problems 120 activities show that top rank optimizing each function under both similar. Based obtained results, produce a schedule high eNPV, cause indicates trade-off between risk. selection best dependent risk-aversion level manager. A risk-averse manager recommended use rule discounted flow weight activity duration statistical at earliest finish time simulation-based policies. But risk-preferent it better cumulative latest