基于仿真的随机活动网络进度费用联合风险

针对复杂随机活动网络活动时间、费用随机性和相关性特点,采用蒙特卡罗方法随机抽取时间、费用样本,再利用乔列斯基因子分解法,将独立分布的时间和费用随机样本转化为相关的随机样本,建立了时间和费用为相关随机变量的随机活动网络仿真模型.通过算例结果的比较分析,说明新模型可以更准确地预测项目的风险概率,进行时间-费用交换分析以及进行项目工期和费用优化.

Simulation based schedule and cost integrated risk of stochastic activity network

Since complex stochastic activity network is characteristic of uncertain activity time and cost, the Monte Carlo simulation method was used to model the stochastic activity network with the correlative stochastic variables of time and cost. Here the method of Cholesky decomposition was used to convert independent distribution of stochastic variables such as time and cost into correlative stochastic variables. A case study is presented in detail to illustrate the validity of the modeling and analysis process. The simulation result reveals the model can accurately and rapidly process the job of time-cost trade-off and obtain optimum project duration and cost.