A partner-selection method based on interval multiplicative preference relations with approximate consistency

In dealing with many new market requirements, partner selection is important for the formation of a virtual enterprise. In this paper, by using the (n - 1) interval pairwise comparisons, a new partner-selection method is proposed, which is based on a new concept of approximate consistency for interval multiplicative preference relations. First, it is pointed out that when the (n - 1) pairwise comparisons are used to construct a complete preference relation, they should form a complete comparison chain beginning with a randomly chosen pair alternatives. Second, the concept of interval multiplicative preference relations with approximate consistency is proposed. Third, a new method of constructing an interval multiplicative preference relation with approximate consistency is presented. A new algorithm is given and a numerical example is carried out to illustrate the proposed approaches and compare with the existing ones.

[1]  W. Ossadnik.  AHP-based synergy allocation to the partners in a merger , 1996 .

[2]  Scott T. Young,et al.  Hospital Materials Management: Systems and Performance , 1989 .

[3]  P. Harker.  Alternative modes of questioning in the analytic hierarchy process , 1987 .

[4]  David J. Barnes,et al.  Partner selection in agile supply chains: a fuzzy intelligent approach , 2014 .

[5]  Alessio Ishizaka,et al.  Review of the main developments in the analytic hierarchy process , 2011, Expert Syst. Appl..

[6]  Zhi-Ping Fan,et al.  A method for partner selection of codevelopment alliances using individual and collaborative utilities , 2010 .

[7]  Fang Liu,et al.  A goal programming model for incomplete interval multiplicative preference relations and its application in group decision-making , 2012, Eur. J. Oper. Res..

[8]  William C. Wedley,et al.  Starting rules for incomplete comparisons in the analytic hierarchy process , 1993 .

[9]  Francisco Herrera,et al.  Some issues on consistency of fuzzy preference relations , 2004, Eur. J. Oper. Res..

[10]  Saadettin Erhan Kesen,et al.  A fuzzy AHP approach to personnel selection problem , 2009, Appl. Soft Comput..

[11]  Alessio Ishizaka,et al.  An expert module to improve the consistency of AHP matrices , 2004 .

[12]  Ludmil Mikhailov,et al.  Fuzzy analytical approach to partnership selection in formation of virtual enterprises , 2002 .

[13]  Yao Zhang,et al.  A goal programming approach to group decision-making with three formats of incomplete preference relations , 2010, Soft Comput..

[14]  Nazario García,et al.  Supplier selection model for commodities procurement. Optimised assessment using a fuzzy decision support system , 2013, Appl. Soft Comput..

[15]  Zhou-Jing Wang,et al.  A note on "A goal programming model for incomplete interval multiplicative preference relations and its application in group decision-making" , 2015, Eur. J. Oper. Res..

[16]  Joseph Sarkis,et al.  Justifying strategic alliances and partnering: a prerequisite for virtual enterprising , 1997 .

[17]  Jonathan Burton,et al.  Application of Analytical Hierarchy Process in Operations Management , 1990 .

[18]  V. M. Rao Tummala,et al.  An application of the AHP in vendor selection of a telecommunications system , 2001 .

[19]  Z. Babic,et al.  Ranking of enterprises based on multicriterial analysis , 1998 .

[20]  Tien-Chin Wang,et al.  Applying consistent fuzzy preference relations to partnership selection , 2007 .

[21]  Zeshui Xu,et al.  Consistency of interval fuzzy preference relations in group decision making , 2011, Appl. Soft Comput..

[22]  R. Hill,et al.  Using the Analytic Hierarchy Process to Structure the Supplier Selection Procedure , 1992 .

[23]  J. Browne,et al.  The extended enterprise-a context for manufacturing , 1998 .

[24]  Fang Liu,et al.  Acceptable consistency analysis of interval reciprocal comparison matrices , 2009, Fuzzy Sets Syst..

[25]  Jian-Bo Yang,et al.  A two-stage logarithmic goal programming method for generating weights from interval comparison matrices , 2005, Fuzzy Sets Syst..

[26]  John J. Kanet,et al.  Application of information technology to a virtual enterprise broker: The case of Bill Epstein , 1999 .

[27]  Didier Dubois,et al.  The role of fuzzy sets in decision sciences: Old techniques and new directions , 2011, Fuzzy Sets Syst..

[28]  Uwe Fink,et al.  Fuzzy Sets Decision Making And Expert Systems , 2016 .