Robust project management with the tilted beta distribution

IF 0.7 4区 数学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE Sort-Statistics and Operations Research Transactions Pub Date : 2015-12-01 DOI:10.13016/M25T3G16R
Eugene D. Hahn, María del Mar López Martín
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引用次数: 9

Abstract

Recent years have seen an increase in the development of robust approaches for stochastic project management methodologies such as PERT (Program Evaluation and Review Technique). These robust approaches allow for elevated likelihoods of outlying events, thereby widening interval estimates of project completion times. However, little attention has been paid to the fact that outlying events and/or expert judgments may be asymmetric. We propose the tilted beta distribution which permits both elevated likelihoods of outlying events as well as an asymmetric representation of these events. We examine the use of the tilted beta distribution in PERT with respect to other project management distributions.
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具有倾斜beta分布的健壮的项目管理
近年来,随机项目管理方法(如PERT(项目评估和评审技术))的稳健方法的发展有所增加。这些健壮的方法允许提高外围事件的可能性,从而扩大项目完成时间的间隔估计。然而,很少有人注意到,外围事件和/或专家判断可能是不对称的。我们提出倾斜的beta分布,它既允许外围事件的可能性升高,也允许这些事件的不对称表示。我们检查了PERT中倾斜beta分布与其他项目管理分布的使用。
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来源期刊
Sort-Statistics and Operations Research Transactions
Sort-Statistics and Operations Research Transactions 管理科学-统计学与概率论
CiteScore
3.10
自引率
0.00%
发文量
0
审稿时长
>12 weeks
期刊介绍: SORT (Statistics and Operations Research Transactions) —formerly Qüestiió— is an international journal launched in 2003. It is published twice-yearly, in English, by the Statistical Institute of Catalonia (Idescat). The journal is co-edited by the Universitat Politècnica de Catalunya, Universitat de Barcelona, Universitat Autonòma de Barcelona, Universitat de Girona, Universitat Pompeu Fabra i Universitat de Lleida, with the co-operation of the Spanish Section of the International Biometric Society and the Catalan Statistical Society. SORT promotes the publication of original articles of a methodological or applied nature or motivated by an applied problem in statistics, operations research, official statistics or biometrics as well as book reviews. We encourage authors to include an example of a real data set in their manuscripts.
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