Mixture densities for project management activity times: A robust approach to PERT

European Journal of Operational Research

Volumn 188, Issue 2, 2008, Pages 450-459

  Hahn, Eugene David ^a  

^a SALISBURY UNIVERSITY   (United States)

Author keywords

Activity times; Beta rectangular distribution; Finite mixture; Outliers; Robust project management

Indexed keywords

DISTRIBUTION FUNCTIONS; FINITE DIFFERENCE METHOD; ROBUST CONTROL; UNCERTAINTY ANALYSIS;

BETA RECTANGULAR DISTRIBUTION; ROBUST PROJECT MANAGEMENT;

PROJECT MANAGEMENT;

EID: 38149045861     PISSN: 03772217     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ejor.2007.04.032     Document Type: Article

References (44)

1. Abdelkader Y.H. Evaluating project completion times when activity times are Weibull distributed. European Journal of Operational Research 157 3 (2004) 704-715
2. Atkinson R., Crawford L., and Ward S. Fundamental uncertainties in projects and the scope of project management. International Journal of Project Management 24 8 (2006) 687-698
3. Azaron A., Katagiri H., Sakawa M., Kato K., and Memariani A. A multi-objective resource allocation problem in PERT networks. European Journal of Operational Research 172 3 (2006) 838-854
4. Banker R.D., and Kauffman R.J. Reuse and productivity in integrated computer-aided software engineering: An empirical study. MIS Quarterly 15 3 (1991) 375-401
5. Bendell A., Solomon D., and Carter J.M. Evaluating project completion times when activity times are Erlang distributed. Journal of the Operational Research Society 46 (1995) 867-882
6. Berger J.O. Statistical Decision Theory and Bayesian Analysis (1985), Springer, New York
7. Bowman R.A. Efficient estimation of arc criticalities in stochastic activity networks. Management Science 41 1 (1995) 58-67
8. Clark C.E. The PERT model for the distribution of an activity time. Operations Research 10 (1962) 405-406
9. Engle R.F. Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50 4 (1982) 987-1007
10. Fama E.F. The behavior of stock-market prices. Journal of Business 38 1 (1965) 34-105
11. Farnum N.R., and Stanton L.W. Some results concerning the estimation of beta distribution parameters in PERT. Journal of Operational Research Society 38 3 (1987) 287-290
12. Gallagher C. A note on PERT assumptions. Management Science 33 10 (1987) 1360
13. Gelman A., Carlin J.B., Stern H.S., and Rubin D.B. Bayesian Data Analysis. second ed. (2003), Chapman and Hall/CRC, Boca Raton, FL
14. Golenko-Ginzburg D. On the distribution of activity time in PERT. Journal of the Operational Research Society 39 8 (1988) 767-771
15. Grant K.P., Cashman W.M., and Christenson D.S. Delivering projects on time. Research Technology Management 49 6 (2006) 52-58
16. Grubbs F.E. Attempts to validate certain PERT statistics or 'Picking on PERT'. Operations Research 10 (1962) 912-915
17. Heller U. On the shortest overall duration in stochastic project networks. Methods of Operations Research 42 (1981) 85-104
18. Hogarth R.M. Cognitive processes and the assessment of subjective probability distributions. Journal of the American Statistical Association 70 (1975) 271-289
19. Johnson D. The triangular distribution as a proxy for the beta distribution in risk analysis. The Statistician 46 3 (1997) 387-398
20. Kadane J.B., Shmueli G., Minka T.P., Borle S., and Boatwright P. Conjugate analysis of the Conway-Maxwell-Poisson distribution. Bayesian Analysis 1 2 (2006) 363-374
21. Kamburowski J. New validations of PERT times. Omega 25 3 (1997) 323-328
22. Keefer D.L., and Bodily S.E. Three-point approximations for continuous random variables. Management Science 29 5 (1983) 595-609
23. Keefer D.L., and Verdini W.A. Better estimation of PERT activity time parameters. Management Science 39 9 (1993) 1086-1091
24. Kotiah T., and Wallace N. Another look at the PERT assumptions. Management Science 20 1 (1973) 44-49
25. Kulkarni V.G., and Adlakha V.G. Markov and Markov-regenerative PERT Networks. Operations Research 34 5 (1986) 769-781
26. Littlefield Jr. T., and Randolph P. An answer to Sasieni's question on PERT times. Management Science 33 10 (1987) 1357-1359
27. MacCrimmon K.R., and Ryavec C.A. An analytical study of the PERT assumptions. Operations Research 12 1 (1964) 16-37
28. Malcolm D.G., Roseboom J.H., Clark C.E., and Fazar W. Application of a technique for research and development program evaluation. Operations Research 7 (1959) 646-669
29. Mandelbrot B.B. The variation of certain speculative prices. Journal of Business 36 4 (1963) 394-419
30. McCullagh P., and Nelder J.A. Generalized Linear Models. second ed. (1989), Chapman and Hall, London
31. McLachlan G.J., and Basford K.E. Mixture Models: Inference and Applications to Clustering (1988), Marcel Dekker, New York
32. Megill R.E. An Introduction to Risk Analysis. second ed. (1984), PennWell Books, Tulsa, OK
33. Mitchell V.L., and Zmud R.W. The effects of coupling IT and work process strategies in redesign projects. Organization Science 10 4 (1999) 424-438
34. Moder J.J., Phillips C.R., and Davis E.W. Project Management with CPM, PERT and Precedence Diagramming. third ed. (1983), Van Nostrand Reinhold, New York
35. Morgenshtern, O., Raz, T., Dvir, D., in press. Empirical analysis in software process simulation modeling. Information and Software Technology.
36. Perry C., and Greig I.D. Estimating the mean and variance of subjective distributions in PERT and decision analysis. Management Science 21 12 (1975) 1477-1480
37. Pleguezuelo R.H., Pérez J.G., and Rambaud S.C. A note on the reasonableness of PERT hypotheses. Operations Research Letters 31 1 (2003) 60-62
38. Premachandra I.M. An approximation of the activity duration distribution in PERT. Computers and Operations Research 28 5 (2001) 443-452
39. Raffo D.M., and Kellner M.I. Empirical analysis in software process simulation modeling. Journal of Systems and Software 53 1 (2000) 31-41
40. Sasieni M.W. A note on PERT times. Management Science 32 12 (1986) 1652-1653
41. Schmidt C.W., and Grossmann I.E. The exact overall time distribution of a project with uncertain task durations. European Journal of Operational Research 126 3 (2000) 614-636
42. Steele M.D., and Huber W.A. Exploring data to detect project problems. AACE International Transactions 32 12 (2004) PM.21.1-PM.21.7
43. Titterington D.M., Smith A.F.M., and Makov U.E. Statistical Analysis of Finite Mixture Distributions (1985), Wiley, Chichester
44. Williams T.M. Practical use of distributions in network analysis. Journal of the Operations Research Society 43 (1992) 265-270