Solving the Resource-Constrained Project Scheduling Problem by Genetic Algorithm(<Special English Issue>Global Supply Chain Management)

抄録

The resource-constrained project scheduling problem (RCPSP) is one of the most difficult challenges in project schedule management. In the previous research work for RCPSP, activity durations in the project are often initially determined by the fixed values (fixed activity durations), and then the optimization process is carried out to assign the optimal start times of activities. In many cases, however, the activity durations vary within the certain ranges (variable activity durations), and depend on the scheduling objective. Thus, it is highly probable that these initially fixed activity durations lead to unexpected results. The way in which the activity durations are reasonably assigned is very important for reducing the overall project duration under resource constraints. For solving the RCPSP with variable activity durations, it is impossible to use the traditional methods (such as CPM, PERT), so the new method based on genetic algorithm (GA) is proposed in this paper for solving the problem. In the proposed method, the genetic algorithm is introduced to determine the optimal activity durations, and the heuristic rules are applied to assign the optimal start time of each activity so that the overall project duration under resource constraints is minimized.