Robust resource-constrained max-NPV project scheduling with stochastic activity duration

This study investigates the robust resource-constrained max-NPV project problem with stochastic activity duration. First, the project net present value (NPV) and the expected penalty cost are proposed to measure quality robustness and solution robustness from the perspective of discounted cash flows, respectively. Then, a composite robust scheduling model is proposed in the presence of activity duration variability and a two-stage algorithm that integrates simulated annealing and tabu search is developed to deal with the problem. Finally, an extensive computational experiment demonstrates the superiority of the combination between quality robustness and solution robustness as well as the effectiveness of the proposed two-stage algorithm for generating project schedules compared with three other algorithms, namely simulated annealing, tabu search, and multi-start iterative improvement method. Computational results indicate that the proactive project schedules with composite robustness not only can effectively protect the payment plan from disruptions through allocating appropriate time buffers, but also can achieve a remarkable performance with respect to the project NPV.