CLC number: TU71
On-line Access: 2012-01-04
Received: 2011-06-10
Revision Accepted: 2011-09-07
Crosschecked: 2011-12-06
Cited: 11
Clicked: 8707
José Luís Ponz-Tienda, Eugenio Pellicer, Víctor Yepes. Complete fuzzy scheduling and fuzzy earned value management in construction projects[J]. Journal of Zhejiang University Science A, 2012, 13(1): 56-68.
@article{title="Complete fuzzy scheduling and fuzzy earned value management in construction projects",
author="José Luís Ponz-Tienda, Eugenio Pellicer, Víctor Yepes",
journal="Journal of Zhejiang University Science A",
volume="13",
number="1",
pages="56-68",
year="2012",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A1100160"
}
%0 Journal Article
%T Complete fuzzy scheduling and fuzzy earned value management in construction projects
%A José Luís Ponz-Tienda
%A Eugenio Pellicer
%A Víctor Yepes
%J Journal of Zhejiang University SCIENCE A
%V 13
%N 1
%P 56-68
%@ 1673-565X
%D 2012
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A1100160
TY - JOUR
T1 - Complete fuzzy scheduling and fuzzy earned value management in construction projects
A1 - José Luís Ponz-Tienda
A1 - Eugenio Pellicer
A1 - Víctor Yepes
J0 - Journal of Zhejiang University Science A
VL - 13
IS - 1
SP - 56
EP - 68
%@ 1673-565X
Y1 - 2012
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A1100160
Abstract: This paper aims to present a comprehensive proposal for project scheduling and control by applying fuzzy earned value. It goes a step further than the existing literature: in the formulation of the fuzzy earned value we consider not only its duration, but also cost and production, and alternatives in the scheduling between the earliest and latest times. The mathematical model is implemented in a prototypical construction project with all the estimated values taken as fuzzy numbers. Our findings suggest that different possible schedules and the fuzzy arithmetic provide more objective results in uncertain environments than the traditional methodology. The proposed model allows for controlling the vagueness of the environment through the adjustment of the α-cut, adapting it to the specific circumstances of the project.
[1]Anbari, F.T., 2003. Earned value project management: Methods and extensions. Project Management Journal, 34(4):12-23.
[2]Bonnai, P., Gourc, D., Lacoste, G., 2004. Where do we stand with fuzzy project scheduling? Journal of Construction Engineering and Management, 130(1):114-123.
[3]Buckley, J.J., Eslami, E., Feuring, T., 2002. Fuzzy mathematics in Economics and Engineering: Studies in Fuzziness and Soft Computing. Physica-Verlag, Heidelberg, Germany.
[4]Chanas, S., Kambourowski, J., 1981. The use of fuzzy variables in PERT. Fuzzy Sets and Systems, 5(1):11-19.
[5]Chen, C.T., Huang, S.F., 2007. Applying fuzzy method for measuring criticality in project network. Information Sciences, 177:2448-2458.
[6]Fleming, Q.W., Koppelman, J.M., 1998. Earned value project management. The Journal of Defense Software Engineering, 16(1):19-23.
[7]Kuchta, D., 2005. Fuzzyfication of the earned value method. WSEAS Transactions on Systems, 4(12):2222-2237.
[8]Laviolette, M., Seaman, J.W., Barrett, J.D., Woodall, W.H., 1995. A probabilistic and statistical view of fuzzy methods. Technometrics, 37(3):249-261.
[9]Lawry, J., 2001. An alternative approach to computing with words. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 9:3-16.
[10]Lipke, W., 2003. Schedule is Different. The Measurable News, March & Summer, p.31-34. Available from http://www.earnedschedule.com/Docs/Schedule%20is%20Different.pdf [Accessed on May 20, 2011].
[11]Lipke, W., Zwikael, O., Henderson, K., Anbari, F.T., 2009. Prediction of project outcome: The application of statistical methods to earned value management and earned schedule performance indexes. International Journal of Project Management, 27(4):400-407.
[12]Liu, Y.C., Yang, S.M., Lin, Y.T., 2010. Fuzzy finish time modeling for project scheduling. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 12(11):946-952.
[13]Moslemi, N.L., Salehipour, A., 2011. Evaluating fuzzy earned value indices and estimates by applying alpha cuts. Expert Systems with Applications, 38(7):8193-8198.
[14]Moslemi, N.L., Shadrokh, S., Salehipour, A., 2011. A fuzzy approach for the earned value management. International Journal of Project Management, 29(6):764-772.
[15]Noori, S., Bagherpour, M., Zareei, A., 2008. Applying fuzzy control charts in earned value analysis: A new application. World Applied Sciences Journal, 3(4):684-690.
[16]Pellicer, E., Pellicer, T.M., Catalá, J., 2009. An integrated control system for SMEs in the construction industry. Revista de la Construcción, 8(2):4-17.
[17]Ponz-Tienda, J.L., 2010. Robust GRCPSP based on Production Processes for Construction Projects. PhD Thesis, Universitat Politècnica de València, Valencia (in Spanish).
[18]Prade, H., 1979. Using fuzzy set theory in a scheduling problem: A case study. Fuzzy Sets and Systems, 2(2):153-165.
[19]Shipley, M., Korvin, A., Omer, K., 1996. A fuzzy logic approach for determining expected values: A project management application. The Journal of the Operational Research Society, 47(4):562-569.
[20]Wang, J., Hao, J., 2007. Fuzzy linguistic PERT. IEEE Transactions on Fuzzy Systems, 15(2):133-144.
[21]Yao, J.S., Wu, K.M., 2000. Ranking fuzzy numbers based on decomposition principle and signed distance. Fuzzy Sets and Systems, 116(2):275-288.
[22]Zadeh, L.A., 1965. Fuzzy sets. Information and Control, 8(3):338-353.
[23]Zadeh, L.A., 1975. The concept of a linguistic variable and its application to approximate reasoning. Part I. Information Sciences, 8(3):199-249.
[24]Zadeh, L.A., 1995. Discussion: Probability theory and fuzzy logic are complementary rather than competitive. Technometrics, 37(3):271-276.
Open peer comments: Debate/Discuss/Question/Opinion
<1>