Available online at sciencedirect

1. ~ Available online at www.sciencedirect.com ..-, S . O. t 1 _-Ii AnJUEI) -.clence Irec ~mE~TgCAL ..MOOELrll~(;, ELSEVIER Applied MathematicalModellingxxx (2007) xxx-xxx www.elsevier.com/iocate/apm 2 A mathematical programming approach for effective supplier 3 ranking in the presence of both cardinal anctorctinal data .* c"""? 4 Reza FarZl p oor Saen c"cc cC"""!;". ":11 cl 5 DepartmentofIndustrialManage~ent.FacultyofManagement Ac~~"lfrI:ffig;!~{qtf/ic and Azad University, ~ 6 Karaj Branch, P.O. Box 31485-313, Kar~~t;Ir~~c:!:!::, . 8 «, ' 7 Received October2006;received revisedfonn 14 July 2QQl;ca~pted11 September 17 in 2007 9 Abstract c,;C*ffi~:;~j; 10 Traditionally, supplier ranking models were based on car4,~nalda~::~ith less emphasis on ordinal data. However, with 11 the widespread use of manufacturing philosophies such as,,,~fist,,Ih- Time (JIT), emphasis has shifted to the simultaneous 12 consideration of cardinal and ordinal data in supplier raqJtirigcpro~§s. To rank the suppliers in the presenceof both car- c Ccc" 13 dinal and ordinal data, this paper proposes an innovatiY~c~pproacn,which is based on Imprecise Data Envelopment Anal- 14 ysis (IDEA). The objective of this paper is to propose a rno,g~l that discussesthe use of IDEA in supplier ranking. A 15 numerical example demonstrates the application 0~;;;tHe'p~,2PO§~d method. 16 @ 2007 Published by Elsevier Inc. :jI1c, '111 ,: '"::!"':!1:::1::::,,:::11 17 Keywords:Supplychainmanagement; Suppliers r~~kin~if"Jm~recise envelopment data analysis; Minimax regret-based approach 18