Uncertain chance-constrained programming model for project scheduling problem
针对活动时长无历史数据、由信念度估计的项目调度问题，构建了三种不确定机会约束规划模型，并转化为清晰形式，用智能算法求解最优调度。
In this paper, we consider an uncertain project scheduling problem, in which activity durations, with no historical data generally, are estimated by belief degrees and assumed to be uncertain variables. To achieve different management goals, we build three uncertain chance-constrained programming models for project scheduling problem, in which the chance constraint must reach a predetermined confidence level. Moreover, these models can all be transformed to their crisp forms, and an intelligent algorithm is designed to search the optimal schedule. Finally, a numerical example is presented to illustrate the usefulness of the proposed model.