Resource Constrained Project Proactive Scheduling to Minimize Uncertainty Cost Considering Information handling

This paper addresses the resource-constrained project proactive scheduling problem with uncertain activity durations considering information handling cost. An proactive optimization model is proposed to derive the information handling cost and the proactive starting time of each activity decisions that minimize the total uncertainty cost of a proactive schedule, which includes an information handling cost for improving standard variance of activity duration, an uncertainty occupation cost of time buffer to renewable resources as well as a mean cost of multiple reactive adjustments, satisfying the project deadline, the renewable resources availability and the precedence constraints. Aiming at the NP-hardness of the problem, three heuristic algorithms are designed, including a Tabu Search, a Variable Neighborhood Search, and a combined program of the two algorithms. Ultimately, an extensive computational experiment is used to show the relative performance of these algorithms and properties. It is shown that a proactive schedule which has less total uncertain cost and certain robustness can be finally obtained by investing information handling cost to decrease the mean cost of multiple reactive adjustments.