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《工程(英文)》 >> 2022年 第9卷 第2期 doi: 10.1016/j.eng.2021.07.019

项目进度管理中基于挣值的随机工期分析

Department of Business Organization and CIM, School of Industrial Engineering, University of Valladolid, Valladolid 47011, Spain

收稿日期: 2020-03-07 修回日期: 2021-06-30 录用日期: 2021-07-27 发布日期: 2021-10-05

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摘要

挣值工期管理(EDM)是一种用于项目进度管理(PSM)的研究方法,当无法使用挣值管理(EVM)时,可以考虑这种方法。挣值工期管理用于估算进度偏差和最终项目工期。挣值工期管理和挣值管理的关键区别在于:在挣值工期管理中,用工作周期表示活动的值;而在挣值管理中,用成本表示活动的值。本文将展示如何使用挣值工期管理监控随机项目。为便于解释该方法,本文通过实例分析对呈现出高度不确定性的项目开展研究,项目中的各项活动采用随机工期。根据这些活动的网络拓扑分析该方法的可用性,并比较了挣值管理和挣值进度分析法(ESM)对项目进度管理的作用。

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参考文献

[ 1 ] Pellerin R, Perrier N. A review of methods, techniques and tools for project planning and control. Int J Prod Res 2019;57(7):2160–78. 链接1

[ 2 ] Vanhoucke M. Tolerance limits for project control: an overview of different approaches. Comput Ind Eng 2019;127:467–79. 链接1

[ 3 ] Fleming QW, Koppelman JM. Earned value project management. 2nd ed. Philadelphia: Project Management Institute; 2000. 链接1

[ 4 ] Practice standard for earned value management. 2nd ed. Philadelphia: Project Management Institute; 2005.

[ 5 ] Anbari FT. Earned value project management method and extensions. Proj Manage J 2003;34(4):12–23. 链接1

[ 6 ] Vanhoucke M. Measuring time: improving project performance using earned value management. Ghent: Springer; 2010. 链接1

[ 7 ] Christensen DS. The estimate at completion problem: a review of three studies. Proj Manage J 1993;24(1):37–42. 链接1

[ 8 ] Kim EH, Wells Jr WG, Duffey MR. A model for effective implementation of earned value management methodology. Int J Proj Manag 2003;21(5):375–82. 链接1

[ 9 ] Lipke W. Schedule is different. The Measurable News 2003;2:31–4. 链接1

[10] Pajares J, López-Paredes A. An extension of the EVM analysis for project monitoring: the cost control index and the schedule control index. Int J Proj Manag 2011;29(5):615–21. 链接1

[11] Acebes F, Pajares J, Galán JM, López-Paredes A. Beyond earned value management: a graphical framework for integrated cost, schedule and risk monitoring. Procedia Soc Behav Sci 2013;74:181–9. 链接1

[12] Khamooshi H, Golafshani H. EDM: earned duration management, a new approach to schedule performance management and measurement. Int J Proj Manag 2014;32(6):1019–41. 链接1

[13] De Andrade PA, Martens A, Vanhoucke M. Using real project schedule data to compare earned schedule and earned duration management project time forecasting capabilities. Autom Construct 2019;99:68–78. 链接1

[14] De Andrade PA, Vanhoucke M. Combining EDM and EVM: a proposed simplification for project time and cost management. J Mod Proj Manag 2017;5(2):94–107. 链接1

[15] Acebes F, Pereda M, Poza D, Pajares J, Galán JM. Stochastic earned value analysis using Monte Carlo simulation and statistical learning techniques. Int J Proj Manag 2015;33(7):1597–609. 链接1

[16] A guide to the project management body of knowledge: PMBOK Guide. 6th ed. Philadelphia: Project Management Institute; 2017.

[17] Acebes F, Pajares J, Galán JM, López-Paredes A. A new approach for project control under uncertainty. Going back to the basics. Int J Proj Manag 2014; 32(3):423–34. 链接1

[18] Hazır Ö. A review of analytical models, approaches and decision support tools in project monitoring and control. Int J Proj Manag 2015;33(4):808–15. 链接1

[19] Rozenes S, Vitner G, Spraggett S. Project control: literature review. Proj Manage J 2006;37(4):5–14. 链接1

[20] Fleming QW, Koppleman JM. Earned value project management. 4th ed. Philadelphia: Project Management Institute; 2010. 链接1

[21] Willems LL, Vanhoucke M. Classification of articles and journals on project control and earned value management. Int J Proj Manag 2015;33(7):1610–34. 链接1

[22] Zadeh LA. Fuzzy sets. Inf Control 1965;8(3):338–53. 链接1

[23] Colin J, Vanhoucke M. A comparison of the performance of various project control methods using earned value management systems. Expert Syst Appl 2015;42(6):3159–75. 链接1

[24] Colin J, Martens A, Vanhoucke M, Wauters M. A multivariate approach for topdown project control using earned value management. Decis Support Syst 2015;79:65–76. 链接1

[25] Colin J, Vanhoucke M. Developing a framework for statistical process control approaches in project management. Int J Proj Manag 2015;33(6): 1289–300. 链接1

[26] Colin J, Vanhoucke M. Setting tolerance limits for statistical project control using earned value management. Omega 2014;49:107–22. 链接1

[27] Martens A, Vanhoucke M. A buffer control method for top-down project control. Eur J Oper Res 2017;262(1):274–86. 链接1

[28] Vanhoucke M. Using activity sensitivity and network topology information to monitor project time performance. Omega 2010;38(5):359–70. 链接1

[29] Vanhoucke M. On the dynamic use of project performance and schedule risk information during project tracking. Omega 2011;39(4):416–26. 链接1

[30] Lee DE. Probability of project completion using stochastic project scheduling simulation. J Constr Eng Manage 2005;131(3):310–8. 链接1

[31] Lee DE, Arditi D. Automated statistical analysis in stochastic project scheduling simulation. J Constr Eng Manage 2006;132(3):268–77. 链接1

[32] Vanhoucke M, Vandevoorde S. A simulation and evaluation of earned value metrics to forecast the project duration. J Oper Res Soc 2007;58(10):1361–74. 链接1

[33] Batselier J, Vanhoucke M. Evaluation of deterministic state-of-the-art forecasting approaches for project duration based on earned value management. Int J Proj Manag 2015;33(7):1588–96. 链接1

[34] Batselier J, Vanhoucke M. Improving project forecast accuracy by integrating earned value management with exponential smoothing and reference class forecasting. Int J Proj Manag 2017;35(1):28–43. 链接1

[35] Wauters M, Vanhoucke M. Study of the stability of earned value management forecasting. J Constr Eng Manage 2015;141(4):04014086. 链接1

[36] Batselier J, Vanhoucke M. Empirical evaluation of earned value management forecasting accuracy for time and cost. J Constr Eng Manage 2015;141(11): 05015010. 链接1

[37] Wauters M, Vanhoucke M. A comparative study of artificial intelligence methods for project duration forecasting. Expert Syst Appl 2016;46:249–61. 链接1

[38] Naeni LM, Shadrokh S, Salehipour A. A fuzzy approach for the earned value management. Int J Proj Manag 2011;29(6):764–72. 链接1

[39] Mortaji STH, Bagherpour M, Noori S. Fuzzy earned value management using L–R fuzzy numbers. J Intell Fuzzy Syst 2013;24(2):323–32. 链接1

[40] Salari M, Bagherpour M, Kamyabniya A. Fuzzy extended earned value management: a novel perspective. J Intell Fuzzy Syst 2014;27(3):1393–406. 链接1

[41] Salari M, Bagherpour M, Hossein Reihani M. A time-cost trade-off model by incorporating fuzzy earned value management: a statistical based approach. J Intell Fuzzy Syst 2015;28(4):1909–19. 链接1

[42] Moradi N, Mousavi SM, Vahdani B. An earned value model with risk analysis for project management under uncertain conditions. J Intell Fuzzy Syst 2017;32(1):97–113. 链接1

[43] Li J, Moselhi O, Alkass S. Forecasting project status by using fuzzy logic. J Constr Eng Manage 2006;132(11):1193–202. 链接1

[44] Wood DA. A critical-path focus for earned duration increases its sensitivity for project-duration monitoring and forecasting in deterministic, fuzzy and stochastic network analysis. J Comput Methods Sci Eng 2018;18(2):359–86. 链接1

[45] Liu S, Lin Y. Grey systems: theory and applications. Berlin: Springer; 2010. 链接1

[46] Mahmoudi A, Bagherpour M, Javed SA. Grey earned value management: theory and applications. IEEE Trans Eng Manage 2021;68(6):1703–21. 链接1

[47] Khamooshi H, Abdi A. Project duration forecasting using earned duration management with exponential smoothing techniques. J Manage Eng 2017; 33(1):04016032. 链接1

[48] Ghanbari A, Taghizadeh H, Iranzadeh S. Project duration performance measurement by fuzzy approach under uncertainty. Eur J Pure Appl Math 2017;10(5):1135–47. 链接1

[49] Ghanbari A, Taghizadeh H, Iranzadeh S. A fuzzy approach for measuring project performance based on relative preference relation. Ind Eng Manag Syst 2017;16(4):486–94. 链接1

[50] Doskocˇil R. An evaluation of total project risk based on fuzzy logic. Bus Theory Pract 2015;17(1):23–31. 链接1

[51] Hamzeh AM, Mousavi SM. A new fuzzy approach for project time assessment under uncertain conditions. In: Bashiri M, Tavakkoli-Moghaddam R, Sabbaghnia A, Valilai OF, Ebrahimi M, Keyanpour M, editors. Proceedings of 15th Iran International Industrial Engineering Conference; 2019 Jan 23–24; Yazd, Iran. New York: Curran Associates; 2019. p. 76–80. 链接1

[52] Hamzeh AM, Mousavi SM, Gitinavard H. Imprecise earned duration model for time evaluation of construction projects with risk considerations. Autom Constr 2020;111:102993. 链接1

[53] Yousefi N, Sobhani A, Naeni LM, Currie KR. Using statistical control charts to monitor duration-based performance of project. J Mod Proj Manag 2019;6(3): 1–26. 链接1

[54] Hodge VJ, Austin J. A survey of outlier detection methodologies. Artif Intell Rev 2004;22(2):85–126. 链接1

[55] Pimentel MAF, Clifton DA, Clifton L, Tarassenko L. A review of novelty detection. Signal Process 2014;99:215–49. 链接1

[56] Markou M, Singh S. Novelty detection: a review–part 2: neural network based approaches. Signal Process 2003;83(12):2499–521. 链接1

[57] Markou M, Singh S. Novelty detection: a review–part 1: statistical approaches. Signal Process 2003;83(12):2481–97. 链接1

[58] Venables WN, Ripley BD. Modern applied statistics with S. New York: Springer; 2002. 链接1

[59] Kuhn M. A short introduction to the caret package. Stat Comput 2015:1–10. 链接1

[60] Brownlee J. Machine learning mastery with R: get started, build accurate models and work through project step-by-step. Melbourne: Machine Learning Mastery; 2016. 链接1

[61] Fisher RA. The use of multiple measurements in taxonomic problems. Ann Eugen 1936;7(2):179–88. 链接1

[62] McLachlan GJ. Discriminant analysis and statistical pattern recognition. Hoboken: Wiley; 2004. 链接1

[63] Wu X, Kumar V, Quinlan JR, Ghosh J, Yang Q, Motoda H, et al. Top 10 algorithms in data mining. Knowl Inf Syst 2008;14(1):1–37. 链接1

[64] Altman NS. An introduction to kernel and nearest-neighbor nonparametric regression. Am Stat 1992;46(3):175–85. 链接1

[65] Cortes C, Vapnik V. Support-vector networks. Mach Learn 1995;20(3):273–97. 链接1

[66] Ho TK. Random decision forests. In: Proceedings of 3rd International Conference on Document Analysis and Recognition; 1995 Aug 14–16; Montreal, QC, Canada. New York: IEEE; 1995. p. 278–82. 链接1

[67] Freedman DA. Statistical models: theory and practice. New York: Cambridge University Press; 2009. 链接1

[68] Chen HL, Chen WT, Lin YL. Earned value project management: improving the predictive power of planned value. Int J Proj Manag 2016;34(1):22–9. 链接1

[69] Chen HL. Improving forecasting accuracy of project earned value metrics: linear modeling approach. J Manage Eng 2014;30(2):135–45. 链接1

[70] Elshaer R. Impact of sensitivity information on the prediction of project’s duration using earned schedule method. Int J Proj Manag 2013;31(4):579–88. 链接1

[71] Zwikael O, Globerson S, Raz T. Evaluation of models for forecasting the final cost of a project. Proj Manage J 2000;31(1):53–7. 链接1

[72] Batselier J, Vanhoucke M. Construction and evaluation framework for a reallife project database. Int J Proj Manag 2015;33(3):697–710. 链接1

[73] projectmanagement.ugent.be [Internet]. Ghent: Operations Research and Scheduling Research Group; [cited 2018 Dec 19]. Available from: http:// www.projectmanagement.ugent.be/research/data/realdata.

[74] Vanhoucke M, Coelho J, Batselier J. An overview of project data for integrated project management and control. J Mod Pro Manag 2016;3(3): 6–21. 链接1

[75] Hammad M, Abbasi A, Chakrabortty RK, Ryan MJ. Predicting the critical path changes using sensitivity analysis: a delay analysis approach. Int J Managing Proj Bus 2020;13(5):1097–119. 链接1

[76] Johnson D. The triangular distribution as a proxy for the beta distribution in risk analysis. J R Stat Soc 1997;46(3):387–98. 链接1

[77] Batselier J, Vanhoucke M. Project regularity: development and evaluation of a new project characteristic. J Syst Sci Syst Eng 2017;26(1):100–20. 链接1

[78] Breiman L. Bagging predictors. Mach Learn 1996;24(2):123–40. 链接1

[79] Breiman L. Random forests. Mach Learn 2001;45(1):5–32. 链接1

[80] James G, Witten D, Hastie T, Tibshirani R. An introduction to statistical learning. New York: Springer; 2013. 链接1

[81] Mika S, Ratsch G, Weston J, Scholkopf B, Mullers KR. Fisher discriminant analysis with kernels. In: Neural Networks for Signal Processing IX. Proceedings of the 1999 IEEE Signal Processing Society Workshop; 1999 Aug 25; Madison, WI, USA. New York: IEEE; 1999. p. 41–8. 链接1

[82] Weinberger KQ, Saul LK. Distance metric learning for large margin nearest neighbor classification. J Mach Learn Res 2009;10:207–44. 链接1

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