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A fuzzy pert approach to evaluate plant construction project scheduling risk under uncertain resources capacity

Journal Name:

  • Journal of Industrial Engineering and Management

Publication Year:

  • 2009
DOI: 
doi:10.3926/jiem.2009.v2n1.p31-47

Key Words:

Author NameUniversity of Author
Abstract (2. Language): 
Abs t rac t : A plant construction project always involves lots of activities. Precise information about the activities duration is unfortunately unavailable due to the uncertain resources capacity. The fuzzy program evaluation and review technique (PERT) has been widely applied to solve the fuzzy project scheduling problem. This paper presents an extended fuzzy PERT approach with four major improvement aspects to support the construction project scheduling management: 1) Evaluate operation fuzzy times based on available working volumes, resources quantity and fuzzy capacity of resources, 2) Adopting a maximal
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  • 1
31-47
  • English

REFERENCES

References: 

Carr, V., & Tah, J.H.M., (2001). A fuzzy Approach to construction project risk
assessment and analysis: construction project risk management system. Advance
in Engineering Software, 32, 847-857.
Yates, J.K., & Eskander, A. (2002). Construction total project management planning
issues. Project Management Journal, 33 (1), 37-48.
Chanas, S., & Zielinski, P. (2001). Critical patch analysis in the network with fuzzy
activity times. Fuzzy Sets and Systems, 122, 195-204.
Lootsma, F.A. (2001). Stochastic and fuzzy PERT. European Journal of Operational
Research, 43(2), 174-183.
Mon, D.L., Cheng, C.H., & Lu, H.C. (1995). Application of fuzzy distributions on
project management. Fuzzy Sets and Systems, 73, 227-234.
Slyeptsov, A.I., & Tyshchuk, T.A. (2003). Fuzzy temporal characteristics of
operations for project management on the network models basis. European
Journal of Operational Research, 147, 253-265.
Dubois, D., Fargier, H., & Galvagnon, V. (2003a). On latest starting times and
floats in activity networks with ill-known durations. European Journal of
Operational Research, 147, 266-280.
Dubois, D., Fargier, H., & Fortemps, P. (2003b). Fuzzy scheduling: Modeling flexible
constraints vs. coping with incomplete knowledge. European Journal of
Operational Research, 147, 231-252.
Wang, J. (1999). A fuzzy set approach to activity scheduling for product
development. Journal of the Operation Research Society, 50, 1217-1228.
Wang, J. (2002). A fuzzy project scheduling approach to minimize schedule risk for
product development. Fuzzy Sets and Systems, 127, 99-116.
Wang, J. (2004). A fuzzy robust scheduling approach for product development
projects. European Journal of Operational Research, 152, 180-194.
Yoon K.P. (1996). A probabilistic approach to rank complex fuzzy numbers. Fuzzy
Sets and Systems, 80, 167-176.
Nezhad, S.S., & Assadi R.G. (2008). Preference ratio-based maximum operator
approximation and its application in fuzzy flow shop scheduling. Applied Soft
Computing, 8, 759-766.

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