Expert judgment in forecasting construction project completion

Emerald - 1997
HASHEMAL‐TABTABAI1, NABILKARTAM1, IANFLOOD2, ALEX P.ALEX1
1Civil Engineering Department, Kuwait University, P.O. Box 5969, Safat 13060, Kuwait
2Assistant Professor, Department of Civil Engineering, University of Maryland, College Park, MD 20742, USA

Tóm tắt

Construction projects are susceptible to cost and time overruns. Variations from planned schedule and cost estimates can result in huge losses for owners and contractors. In extreme cases, the viability of the project itself is jeopardised as a result of variations from baseline plans. Hence new methods and techniques which assist project managers in forecasting the expected variance in schedule and cost should be developed. This paper proposes a judgment‐based forecasting approach which will identify schedule variances from a baseline plan for typical construction projects. The proposed forecasting approach adopts multiple regression techniques and further utilises neural networks to capture the decision‐making procedure of project experts involved in schedule monitoring and prediction. The models developed were applied to a multistorey building project under construction and were found feasible for use in similar construction projects. The advantages and limitations of these two modelling process for prediction of schedule variance are discussed. The developed models were integrated with existing project management computer systems for the convenient and realistic generation of revised schedules at appropriate junctures during the progress of the project.

Từ khóa


Tài liệu tham khảo

ASCE, 1996, ANNs for Civil Engineers: Fundamentals and Applications

Brehmer B., 1987, Wright & P. Ayton), 199

Carpenter W.C., 1995, March, 3, 0

Caudill M., 1989, Feb., 61

10.1016/0263-7863(92)90069-L

Flood I., 1994, ASCE, 8, 131

10.1126/science.194.4263.389

Hammond, K.R., McClelland, G.H. & Mumpower, J. (1980) Human judgment and decision making: theories, methods and procedures, p.258. Praeger, New York.

Lippmann R.P., 1987, An introduction to computing with neural nets, 10.1109/MASSP.1987.1165576

10.1061/(ASCE)0733-9364(1991)117:4(606)

Rumelhart, D.E., Hinton, G.E. & Williams, R.J. (1986) Learning internal representation by error propagation. In Parallel Distributed Processing (eds D.E. Rumelhart,J.L.McClelland and the PDP Research group), pp.318-362. MTT Press, Cambridge, MA.

Scheaffer R.L., 1990, Probability and Statistics for Engineers, 3

10.1016/0263-7863(85)90042-0

Sipos A., 1992, Cost Engineering, 34, 9

10.1037/h0070288

Twomey J.M., 1996, I. Flood & J. Garrett)

Thông tin
Thông tin xuất bản

Emerald

Thông tin tác giả