A type-2 fuzzy set model for contractor prequalification

Abstract Prequalification helps decision makers find the right contractor for the job, which is key to the successful delivery of a construction project. The procedure involves judging the suitability, capability and competency of the contractor on various criteria, using both anecdotal and empirical evidence. The evidence used is often imprecise and subjective, and so is the evaluation and decision making procedure. Type-1 fuzzy sets have been used in the prequalification procedure to handle uncertain information. However, type-1 fuzzy sets are unable to reflect the differences in opinion among experts involved in group decision making. The purpose of this paper is to propose a practical prequalification procedure that uses interval type-2 fuzzy sets to address both linguistic imprecision and differences of opinion. A numerical example shows how the proposed procedure is carried out and the benefits that result compared to a similar procedure using type-1 fuzzy sets.

[1]  H. M. Alhumaidi,et al.  Construction Contractors Ranking Method Using Multiple Decision-Makers and Multiattribute Fuzzy Weighted Average , 2015 .

[2]  Edyta Plebankiewicz A fuzzy sets based contractor prequalification procedure , 2012 .

[3]  Jerry M. Mendel,et al.  Aggregation Using the Linguistic Weighted Average and Interval Type-2 Fuzzy Sets , 2007, IEEE Transactions on Fuzzy Systems.

[4]  Tiesong Hu,et al.  A fuzzy neural network approach for contractor prequalification , 2001 .

[5]  Sławomir Biruk,et al.  Assessing contractor selection criteria weights with fuzzy AHP method application in group decision environment , 2010 .

[6]  Van Uu Nguyen,et al.  Tender evaluation by fuzzy sets , 1985 .

[7]  Miroslaw J. Skibniewski,et al.  DECISION CRITERIA IN CONTRACTOR PREQUALIFICATION , 1988 .

[8]  Hemanta Doloi,et al.  Analysis of pre‐qualification criteria in contractor selection and their impacts on project success , 2009 .

[9]  Jerry M. Mendel,et al.  A comparative study of ranking methods, similarity measures and uncertainty measures for interval type-2 fuzzy sets , 2009, Inf. Sci..

[10]  Edyta Plebankiewicz,et al.  Modelling decision-making processes in bidding procedures with the use of the fuzzy sets theory , 2014 .

[11]  E. Plebankiewicz,et al.  Simple Prequalification Models , 2010 .

[12]  Jerry M. Mendel,et al.  Type-2 fuzzy logic systems , 1999, IEEE Trans. Fuzzy Syst..

[13]  Edyta Plebankiewicz Construction contractor prequalification from polish clients’ perspective , 2010 .

[14]  Gary David Holt,et al.  Contractor selection innovation: examination of two decades' published research , 2010 .

[15]  Ka Chi Lam,et al.  Decision support system for contractor pre-qualification : artificial neural network model , 2000 .

[16]  Lotfi A. Zadeh,et al.  The Concepts of a Linguistic Variable and its Application to Approximate Reasoning , 1975 .

[17]  Edyta Plebankiewicz,et al.  Contractor prequalification model using fuzzy sets , 2010 .

[18]  Jeffrey S. Russell,et al.  QUALIFIER-1: CONTRACTOR PREQUALIFICATION MODEL , 1990 .

[19]  Ana Nieto-Morote,et al.  A fuzzy multi-criteria decision making model for construction contractor prequalification , 2012 .

[20]  Hassan Hosseini Nasab,et al.  A fuzzy multiple-criteria decision-making model for contractor prequalification , 2015, J. Decis. Syst..

[21]  Shyi-Ming Chen,et al.  Fuzzy decision making systems based on interval type-2 fuzzy sets , 2013, Inf. Sci..

[22]  Miroslaw J. Skibniewski,et al.  Qualifier-2: Knowledge-Based System for Contractor Prequalification , 1990 .

[23]  Jerry M. Mendel,et al.  Interval Type-2 Fuzzy Logic Systems Made Simple , 2006, IEEE Transactions on Fuzzy Systems.

[24]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[25]  Khaled Nassar,et al.  Prequalification of Egyptian construction contractors using fuzzy‐AHP models , 2013 .

[26]  S. Thomas Ng,et al.  EQUAL: a case-based contractor prequalifier , 2001 .

[27]  Jian-Bo Yang,et al.  Applying Evidential Reasoning to Prequalifying Construction Contractors , 2002 .

[28]  Jerry M. Mendel,et al.  Enhanced Interval Approach for Encoding Words Into Interval Type-2 Fuzzy Sets and Its Convergence Analysis , 2012, IEEE Transactions on Fuzzy Systems.