A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics

被引：154

作者：

Senthil, S. ^{[1
]}

Srirangacharyulu, B. ^{[2
]}

Ramesh, A. ^{[3
]}

机构：

[1] Kamaraj Coll Engn & Technol, Dept Mech Engn, Virudunagar 626001, India

[2] Indian Inst Management Tiruchirappalli, Tiruchirappalli 620015, Tamil Nadu, India

[3] Natl Inst Technol Calicut, Dept Mech Engn, Calicut 673601, Kerala, India

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2014年 / 41卷 / 01期

关键词：

Reverse logistics; AHP; TOPSIS; Multi-criteria decision making; SUPPLIER SELECTION; FUZZY TOPSIS; MODEL; PROVIDER; MANAGEMENT; DESIGN; ANP;

D O I：

10.1016/j.eswa.2013.07.010

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Due to green legislations, industries track the used products through reverse logistics contractors. A reverse logistics programme offers significant cost savings in procurement, transportation, disposal and inventory carrying. Since reverse logistics operations and the supply chains they support are considerably more complex than traditional manufacturing supply chains, it can be offered to third party contractors. But availability of more number of contractors make evaluating and selecting the most efficient Reverse Logistics Contractor (RLC) a challenging task and treated as a multi-criteria decision making problem. In this paper, a hybrid method using Analytical Hierarchy Process (AHP) and the Fuzzy Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) is proposed. AHP is used to obtain the initial weights and Fuzzy TOPSIS is used to get the final ranking. A case study demonstrates the application of the proposed method. Finally sensitivity analysis is carried out to confirm the robustness. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：50 / 58

页数：9

共 48 条

[41]

Rogers D.L., 2001, J BUS LOGIST, V22, P129, DOI [10.1002/j.2158-1592.2001.tb00007.x, DOI 10.1002/J.2158-1592.2001.TB00007.X]

[42]

SAATY Thomas L., 1989, Fundamentals of Decision Making and Priority Theory, P59, DOI [10.1007/978-3-642-50244-6_4, DOI 10.1007/978-3-642-50244-6_4, 10.1007/978-3-642-50244-64, DOI 10.1007/978-3-642-50244-64]

[43]

Schwartz B., 2000, Transportation and Distribution, V41, P95, DOI DOI 10.1057/PALGRAVE.JORS.2602035

[44] Pricing decisions with retail competition in a fuzzy closed-loop supply chain [J].

Wei, Jie ;

Zhao, Jing .

EXPERT SYSTEMS WITH APPLICATIONS, 2011, 38 (09) :11209-11216

[45] The role of supplier operational adaptation on the performance of IT-enabled transport logistics under environmental uncertainty [J].

Wong, Christina W. Y. ;

Lai, Kee-hung ;

Ngai, E. W. T. .

INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2009, 122 (01) :47-55

[46] FUZZY SETS [J].

ZADEH, LA .

INFORMATION AND CONTROL, 1965, 8 (03) :338-&

[47] Green supply chain management implications for "closing the loop" [J].

Zhu, Qinghua ;

Sarkis, Joseph ;

Lai, Kee-hung .

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW, 2008, 44 (01) :1-18

[48] Simulation based fuzzy TOPSIS approach for group multi-criteria supplier selection problem [J].

Zouggari, Akram ;

Benyoucef, Lyes .

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2012, 25 (03) :507-519

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