基于随机S曲线的项目绩效监测和预测研究  

Research on Monitoring and Forecasting of Project Performance Based on Stochastic S Curves

作　　者：徐哲[1] 汪阳青[1] 王舒[1] 

机构地区：[1]北京航空航天大学经济管理学院,北京100083

出　　处：《系统仿真学报》2009年第4期1187-1191,1194,共6页Journal of System Simulation

基　　金：国家自然科学基金面上项目(70871004);航空科技创新基金项目(07E51009);北航青年创新基金项目

摘　　要：随机S曲线(SS曲线)充分考虑了项目费用和工期的随机性,展示了费用、工期和项目进展百分比之间的关系。基于仿真获得的SS曲线,提出新的费用偏差(CV)和工期偏差(SV)参数,实现对项目绩效的监测;考虑项目未来绩效与过去绩效之间的相关性,依据活动或项目的费用绩效指数(CPI)和工期绩效指数(SPI),对尚未完成和尚未开始活动的费用和时间参数进行调整,采用仿真方法预测项目未来绩效,获得项目完成时费用偏差(CVAC)和工期偏差(SVAC)指标,实现对项目绩效的预测。结合一个三层住宅工程案例,详细说明了基于SS曲线的项目绩效监测和预测方法在项目管理实践中的应用。Stochastic S curves （SS curves） consider about the probabilistie characteristics of cost and duration, and show the relationship between cost, duration and project progress. Based on SS curves, new parameters of cost variation （CV） and schedule variation （SV） were proposed to realize the monitoring of project performance. Considering the correlation between the past performance and the future performance, according to the cost performance indices （CPI） and schedule performance indices （SPI） of actives or project, the cost and time parameters of the activity which was in process or which was not started were adjusted. Then, using the simulation method, the cost variation at completion （CVAC） and the schedule variation at completion （SVAC） were obtained, and the forecasting of project performance was realized Finally, a case study involving a 3-story housing project was performed to verify the capability and utility of the new method of performance monitoring and forecasting based on SS curves in the real world.

关 键 词：费用与进度联合控制 SS曲线 项目绩效监测 项目绩效预测 MONTE Carlo仿真 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] N945.13[自动化与计算机技术—计算机科学与技术]