Fuzzy Approach to Prequalifying Construction Contractors
Publication: Journal of Construction Engineering and Management
Volume 133, Issue 1
Abstract
Construction contractor prequalification (CCPQ) is a crucial decision making process to select capable potential bidders and ensure the success of construction projects. The purpose of CCPQ is to guarantee a contractor’s characteristic to meet the construction project’s requirements, which has been established worldwide as a standard practice. However, existing methods, i.e., marking method, subjective judgment method, etc., for contractor prequalification have been inadequate because it is difficult for decision makers to investigate contractor’s capabilities against inexact, vagueness, and qualitative criteria. The objective of this paper is to propose a fuzzy framework-based fuzzy number theory to solve construction contractor prequalification issues, which include decision criteria analysis, weights assessment, and decision model development. Finally, a case study for a tunnel construction project was used to demonstrate the feasibility of fuzzy approaches.
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References
Bubshait, A. A., and Al-Gobali, H. (1996). “Contractor prequalification in Saudi Arabia.” J. Manage. Eng., 12(2), 50–54.
Chaudhuri, B. B., and Rosenfeld, A. (1996). “On a metric distance between fuzzy sets.” Pattern Recogn. Lett., 17(11), 1157–1160.
Chen, C. T. (1998). “A study of fuzzy group decision-making method.” 6th National Conf. on Fuzzy Theory and Its Applications.
Chen, C.-T. (2001). “A fuzzy approach to select the location of the distribution center.” Fuzzy Sets Syst., 118(1), 65–73.
Chen, S. (1994). Fuzzy system decision-making theory and its application, University of Technology Press, Dalian, China (in Chinese).
Chen, S. (1996a). “Non-structured decision making analysis and fuzzy optimum seeking theory for multi-objective systems.” Journal of Fuzzy Mathematics, 4(2), 835–842.
Chen, S. J., and Hwang, C. L. (1992). Fuzzy multiple attribute decision making: Methods and application, Springer, New York.
Cheng, C.-H., and Lin, Y. (2002). “Evaluating the best main battle tank using fuzzy decision theory with linguistic criteria evaluation.” Eur. J. Oper. Res., 142(1), 174–186.
Gonzalez, A. (1990). “A study of the ranking function approach through mean values.” Fuzzy Sets Syst., 35(1), 29–41.
Groenen, P. J. F., and Jajuga, K. (2001). “Fuzzy clustering with squared Minkowski distances.” Fuzzy Sets Syst., 120(2), 227–237.
Heilpern, S. (1997). “Representation and application of fuzzy numbers.” Fuzzy Sets Syst., 91(2), 259–268.
Holt, G. D., et al. (1994). “Evaluating prequalification criteria in contractor selection.” Build. Environ., 29(4), 437–448.
Hsu, H. M., and Chen, C. T. (1994). “Fuzzy hierarchical weight analysis model for multicriteria decision problem.” J. Chinese Inst. Indust. Engs.., 11(3), 129–136.
Kaufmann, A., and Gupta, M. M. (1988). Fuzzy mathematical models in engineering and management science, North-Holland, Amsterdam, The Netherlands.
Kaufmann, A., and Gupta, M. M. (1991). Introduction to fuzzy arithmetic theory and application, Van Nostrand Reinhold, New York.
Klir, G. J., and Yan, B. (1995). Fuzzy sets and fuzzy logic theory and applications, Prentice-Hall, London.
Li, Y., Chen, S., and Nie, X. (2005). “Fuzzy pattern recognition approach to construction contractor selection.” Fuzzy Optimization and Decision Making, 6(2), 103–118.
Lin, C.-T., and Chen, Y.-T. (2004). “Bid/no-bid decision making-a fuzzy linguistic approach.” Int. J. Proj. Manage., 22(7), 585–593.
Mabuchi, S. (1988). “An approach to the comparison of fuzzy subsets with an a-cut dependent index.” IEEE Trans. Syst. Man Cybern., 18(2), 264–272.
Ng, S. T. (1996). “Case-based reasoning decision support for contactor prequalification.” Ph.D. thesis, University of Manchester, Manchester, U.K.
Russell, J. S., and Skibniewski, M. J. (1988). “An expert system for contractor prequalification.” Proc., Conf. on Computing in Civil Engineering, 239–247.
Russell, J. S., and Skibniewski, M. J. (1990). “QUALIFIER-1: Contractor prequalification model.” J. Comput. Civ. Eng., 4(1), 77–90.
Schmucker, K. J. (1985). Fuzzy sets, nature language computation, and risk analysis, Computer Science Press.
Sengupta, K. (1998). “Fuzzy preference and Orlovsky choice procedure.” Fuzzy Sets Syst., 93(2), 231–234.
Singh, D., and Tiong, R. L. K. (2005). “A fuzzy decision framework for contractor selection.” J. Constr. Eng. Manage., 131(1), 62–70.
Sönmez, M., Holt, G. D., Yang, J. B., and Graham, G. (2002). “Applying evidential reasoning to prequalifying construction contractors.” J. Manage. Eng., 18(3), 111–119.
Triantaphyllou, E., and Lin, C.-T. (1996). “Development and evaluation of five multiattribute decision making methods.” Int. J. Approx. Reason., 14(4), 281–310.
Tsao, C.-T. (2003). “Evaluating investment values of commercial bank stocks using a fuzzy TOPSIS approach.” Journal of Information & Optimization Sciences, 24(2), 373–396.
Yager, R. R. (1981). “A procedure for ordering fuzzy subsets of the unit interval.” Inf. Sci. (N.Y.), 24, 141–161.
Zadeh, L. A. (1965). “Fuzzy sets.” Infect. Control, 8, 338–353.
Zadeh, L. A. (1973). “The concept of a linguistic variable and its application to approximate reasoning.” ERL-M 411, Berkeley, Calif.
Zimmermann, H. J. (1991). Fuzzy set theory and its applications, 2nd ed., Kluwer Academic, Dordrecht, The Netherlands.
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© 2007 ASCE.
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Received: Nov 19, 2004
Accepted: Mar 24, 2006
Published online: Jan 1, 2007
Published in print: Jan 2007
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