具有不确定网络结构的项目建模的宏观方法

M. Liberatore, B. Pollack-Johnson
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引用次数: 4

摘要

本文提出了一种在网络层面而不是在活动层面对项目不确定性进行建模和分析的方法。该方法适用于项目进度风险分析和应急计划。建议的方法要求能够确定一组项目网络情景,每个情景都有一个评估的发生概率。这些场景可能根据在项目初期可能发生的不确定事件、不确定活动持续时间、有限循环或这些事件的组合的结果而有所不同。在本文中,我们提出了一种建模和分析网络场景集的通用方法。我们的方法的一个优点是,它使用标准的方法,如关键路径分析和概率分析,来解决具有不确定网络结构的项目规划问题。我们的方法还带来了不确定性度量,包括预期的和有条件的活动临界松弛,以及由循环导致的重复活动的早开始和晚结束时间。第二个好处是在项目计划中使用不确定性分析的更大的可访问性和可能性,因为数据需求和分析集中在产生进度不确定性的关键场景上。给出了几个示例来说明所建议的方法,包括随机事件、循环和随机活动时间。对未来研究的建议包括实地测试所提出的方法,并确定在何种条件下更适合模拟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A macro approach to modeling projects with uncertain network structures
This paper presents an approach for modeling and analyzing project uncertainty at the network, rather than at the activity, level. This approach is applicable for project schedule risk analysis and contingency planning. The suggested approach requires that a set of project network scenarios be able to be identified, each with an assessed probability of occurrence. These scenarios might differ according to the results of uncertain events that could occur during the coarse of the project, uncertain activity durations, finite loops, or a combination of these. In this paper we present a general approach for modeling and analyzing the set of network scenarios. An advantage of our approach is that it uses standard methods, such as critical path analysis and probability analysis, to solve project planning problems with uncertain network structures. Our approach also leads uncertainty measures, including expected and conditional activity criticality slack, and early and late start and finish times for repeated activities resulting from looping. A second benefit is greater accessibility and likelihood of the use of uncertainty analysis in project planning, since the data needs and the analysis are focused on the key scenarios deriving schedule uncertainty. Several examples are presented to illustrate the proposed approach, including random events, loops, and random activity times. Suggestions for future research include field testing the proposed approach and determining the condition under which it is preferable to simulation.
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