A stochastic scheduling for distributed multi-project with multi-PR heuristic

In the distributed multi-project scheduling problem with uncertain duration, a dynamic scheduling algorithm based on multi-priority-rule heuristic is proposed to minimize the expected total tardiness cost. At each decision point, different multi-priority-rule heuristics are used to determine candidate activities and coordinate global resource conflicts among candidate activities, respectively. Moreover, considering the strategic behavior of information disclosure of managers, a payment negotiation process is designed to counter the opportunistic behavior of managers in the two-project problems. Based on a comprehensive computational study, the results show that the proposed algorithm can effectively reduce the expected total tardiness cost under five kinds of activity duration distribution, and update the optimal results in relevant studies under the constant duration distribution. Additionally, the experiment also analyzes the impact of the strategic behavior of managers in the negotiation process on the multi-project scheduling. From the perspective of cost, the dominant strategy of managers and the corresponding multi-project scheduling solution quality are also studied.