بررسی اندازه گیری میزان پیشرفت فیزیکی پروژه خط لوله انتقال اتیلن با رویکرد فازی

Abstract
Today s the knowledge of project progress rate is the project manager”s challenges, in
the way that while presenting reports the thorough knowledge of project progress
actual rate is a vital matter. One of the crucial matters in project progress
measurement is assigning the weight of any activity in all projects. There are
different criteria in assigning activities weight , but in most of these projects there is
just two factors, time and cost, and this lead to this, that calculated percent of
progress be far from reality. So it is necessary to present a way in which the
measurement project progress rate be more near to reality. Our purpose in this article
is calculating project progress with a comprehensive look and with keeping all
progress effective criteria in mind, to satisfy project”s management by presenting real
data. In presented algorithm for all four phases, theoretical, plan and planning,
performing and completing, we recognize indexes that can be used in calculating the
weight of every activities and in whole project, then calculate the weight of any
activity of all project and finally the real progress rate of all project using Fuzzy
Multiple criteria decision making models. Also in explaining presented model, we
show practical project that use this way to estimate project progress rate.

فهرست منابع انگلیسی
Bagherpour.M, Solimanpur.M ,Faculty of Engineering:Project Weights
Estimation Using an AHP-based Method and Fuzzy Rule Base, , Urmia
University., Iran University of Science & Technology.(2006).
Buckley, J.J. (1985), Fuzzy hierarchical analysis, Fuzzy Sets and Systems,
۱۷(۳), ۲۳۳-۲۴۷.
Chang, D.Y. (1996), Applications of the extent analysis method on fuzzy
AHP, European Journal of Operational Research, 95(3), 649–655.
Cheng ,Ching-Hsue & Lin , Yin .(2002) Evaluating The Best Main Battle
Tank Using Fuzzy Decision Theory with Linguistic Criteria Evaluation
European Journal of Operational Research , Vol.142 ,p 147
Chen, S.J., Hwang, C.L. and Hwang, F.P. (1992), Fuzzy multiple attribute
decision making:Methods and Applications. Lecture Notes in Economics and
Math. Syst., 375, Springer-Verlag, Berlin – Heidelberg.p.1-5
Chen, C.T. 2000. Extensions of the TOPSIS for group decision-making
under fuzzy environment. Fuzzy Sets and Systems, 114, 1-9.
Chu, T. C., & Lin, Y. C. (2003). A fuzzy TOPSIS method for robot
selection. International Journal of Advanced Manufacturing Technology, 21(4),
۲۸۴–290.
Csutora, R., Buckley, J.J. (2001), “Fuzzy hierarchical analysis: the Lambda-
Max method”s”, Fuzzy Sets and Systems, 120(2), 181-95.
Dalkey ,Norman & Helman , Olaf (1963) An Experimental Application of
the Delphi Method to the Use of Experts : Management Science , Vol.9, No.3,
p.458
kerzner, Harold, Project Management, john Wiley & Sons, Inc, 2006
K-Jun Zhu,Yu Jing, Da-Yong Chang ,”A discussion on Extent Analysis
Method and applications of fuzzy AHP “ ,European Journal of Operational
Research 116 (1999) 450
Liang G.S., Fuzzy MCDM based on ideal and anti-ideal concepts, European
Journal of Operational Research 112, 682–691, (1999).
Lipke W. Earned Schedule Leads to Improved Forecasting.17th IPMC
Tyson scorner, VA. 2005 (November)
Lipke.W., Schedule is different, The measurable News, 2003(March).4-31)
Lu, J., Wu, F., Zhang, G. On a generalized fuzzy goal optimization for
solving fuzzy multi-objective linear programming problems, Journal of Intelligent
and Fuzzy Systems, 18 (1), pp. 83-97. 2007
http://iospress.metapress.com/content/6j83284buqgrgt56/fulltext.pdf
Ming Zhou ,”Fuzzy model and optimization models for implementing
QFD”,Computers Ind.Engng ,35. 1-2(1998).237-240
Nufer Yasin Ates, Sezi Cevik, Cengiz Kahremman ,Murt Gulbay , S.Ayca
Erdogan :Multi Attribute Performance Evaluation Using a Hierarchial Fuzzy
TOPSIS Method :Istanbol Technical University , Department of Industrial
Enginering 34367 Mackalstanbul ,Turkey ,(2006).
T.C. Chu, Selecting plant location via a fuzzy TOPSIS approach, The
International Journal of Advanced Manufacturing Technology 20 (2002) 859–864.
Tsaur, S.H., Chang, T.Y., Yen, C.H., (2002). The evaluation of airline
service quality by fuzzy MCDM. Tourism Management, 23, 107-115.
Van Laarhoven, P.J.M., and Pedrycz, W. (1983), A fuzzy extension of
Saaty’s priority theory, FuzzySets and Systems, 11(3), 229-241.
Vandervoorde S, Vanhouke Mario, A comparison of different project
duration forecasting methods using earned value metrics, International journal of
Project Management 24, 2006, 289-302
Xiaonan Zhang , Nick Bakis ,Timothy C. Lukins ,Yahaya M. Ibrahim ,
Song Wu , Mike Kagioglou ,Ghassan Aouad, Ammar P. Kaka, Emanuele Trucco.
Automating progress measurement of construction projects.www. elsevier.com,
Automation in Construction. (2009) 294–301.
Zeleny.M,”Multiple Criteria Decision Making “, McGraw-Hill (1982), New
York.