Proactive Project Scheduling With Activity Splitting and Resource Transfer Times Under Uncertain Environments

Proactive project scheduling aims to generate robust baseline schedules that are protected against the potential schedule disruptions during project execution. In this paper, we propose a new problem named the proactive resource-constrained project scheduling problem with activity splitting and resource transfer times, and try to investigate the trade-off between the benefits of activity splitting and the drawbacks of the resulting more resource transfer times. The proposed problem is formulated into an integer programming model with considering the constraints of a maximum allowed number of splitting and a minimum period of continuous execution. Since the problem is NP-hard in the strong sense, a genetic algorithm is then developed for problem solving. From the obtained results of a designed computational experiment, we prove that the developed genetic algorithm is effective in solving the defined problem, and the benefits of activity splitting to schedule robustness improvement can be weaken with the resulting more resource transfer times among the subactivities. Besides, with the increase of the maximum allowed number of activity splitting, the decrease of the minimum continuous execution time, the decrease of resource transfer times, and the extension of project deadlines, schedule robustness increases.