可打断项目组合选择问题局部敏感性分析

项目组合中各个项目的投资和收益等数据往往通过预测和估算得来,数据的不准确性会给企业决策带来很大风险.因此,企业需要分析参数变化情况对项目组合经济效果的影响,为企业风险防范提供依据.文章首先提出了一个考虑参数变动的可打断项目组合新模型,在其基础上,又提出不考虑可打断项目组合选择模型,然后给出一个算例,通过GAMS/BARON对模型求解,并进一步计算敏感性系数,对参数进行局部敏感性分析,并对各参数的敏感性大小进行了比较,进而对比考虑可打断与不考虑可打断情况下参数不同变动幅度下的敏感性大小.研究结果表明:不同参数变动相同比例时,各参数的敏感性系数大小不同.此外,可打断会对敏感性系数大小产生较大影响.通过敏感性系数大小比较能够确定各参数的重要程度,该结果对企业预防风险和决策具有很好的现实意义.

The local sensitivity analysis of project portfolio selection problem with divisibility

The data about investment and benefit of every project is often acquired by estimating and forecasting. When external environment changes, inaccuracy of the data will bring great risk to the enterprise decision. So we need to analyze how the range of parameters makes influence on the economic benefits. This will provide an important basis to the enterprise in preventing risk. This paper first presents a new model for project portfolio selection problem with divisibility and parameter variation. On the basis of this model, we also present a new model for project portfolio selection problem with parameter variation without divisibility, and then a numerical example is provided and solved by GAMS/BARON. Similarity, we also calculate sensitivity coefficients on the basis of the solution. After that, we make local sensitivity analysis on several important parameters. We also compare the size of parametric sensitivity when considering the divisibility or not considering it. The research results show that:when different parameters vary the same proportion, the size of each parametric sensitivity coefficient is different. Besides, divisibility makes a great influence on the size of sensitivity coefficient. Sensitivity coefficient can reflect the degree of importance of parameters. This has good practical significance in decision-making and risk prevention for enterprise.