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基于蒙特卡罗仿真法的研究型项目风险量化分析技术 被引量:6

Risk Quantification and Analysis for the Research-typed Projects Based on MCS Method
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摘要 科学研究型项目的执行过程正逐步走向规范化、信息化、科学化和理性化,这就要求项目风险的评估和量化方式必须深入,不仅需要分析此类项目风险的重要度排序,还必须分析相关项目风险将会对进度和成本造成的影响,也就是对研究型项目进行风险量化管理。本文着重研究面向研究型项目的风险量化技术,提出了基于蒙特卡罗仿真法的项目定量风险量化技术,基于三角分布模型构建了相关风险数据的采集与处理方法,基于最早开始时间和最早完成时间构建了项目周期模型,基于成本分解结构构建了项目成本模型,在此基础上,定义了基于蒙特卡洛仿真的抽样算法与流程,并提出了相关概率风险误差的分析方法。在风险量化的基础上提出了分层次的项目风险分析方法,针对总项目进度风险,提出了面向指定工期约束的项目相应完工概率计算方法,同时基于关键度指标,提出了面向子项目进度风险的分析方法。 With standardization, informatization, scientificness, and rationalization are more and more popular in the research project management, the risk management becomes more and more important. In risk management, risks in research project should be ordered by their importance, and the influence of risks on project schedule and cost should be also analyzed. A Monte Carlo Simulation (MCS)- based method for quantifying the risk in research project is developed in order to analyze the importance, schedule as well as the cost of the project. Firstly, the method for risk data capturing and processing is developed on basis of the triangle distribution. Secondly, the circle and cost models are developed separately on basis of Earliest Start Time (EST), Earliest Finish Time (EFT) as well as the Cost Breakdown Structure (CBS). Thirdly, the sampling algorithm and flow based on MCS is defined, the analysis method for probabjlistic risk error is also proposed. Finally, a leveled risk analysis method is also developed on basis of the risk quantification; the total risk is divided into the risk of project and risks of subprojects. A method for computing completion probability of appointive deadline constraint-oriented project is discussed; in the meantime, the method for analyzing subproject progress-oriented risks is developed by using the index of key targets which are Key Probability (KP) and Key Importance (KI).
作者 高建伟
出处 《科技导报》 CAS CSCD 北大核心 2012年第13期31-35,共5页 Science & Technology Review
基金 西北工业大学政策研究基金重点项目(ZYZ201102)
关键词 风险 量化 蒙特卡洛 科学研究课题 risk quantification Monte Carlo Simulation research project
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