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

被引:148
|
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
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
收藏
页码:50 / 58
页数:9
相关论文
共 50 条
  • [31] Multi-criteria Decision Making for Job Selection
    Rahman, Mushfiqur
    Asadujjaman, Md
    [J]. 2021 INTERNATIONAL CONFERENCE ON DECISION AID SCIENCES AND APPLICATION (DASA), 2021,
  • [32] Benefits, risks, selection criteria and success factors for third-party logistics services
    Selviaridis K.
    Spring M.
    Profillidis V.
    Botzoris G.
    [J]. Maritime Economics & Logistics, 2008, 10 (4) : 380 - 392
  • [33] An integrated multi-criteria decision-making methodology for conveyor system selection
    Jiamruangjarus, Pairat
    Naenna, Thanakorn
    [J]. COGENT ENGINEERING, 2016, 3 (01):
  • [34] Selection of disposal contractor by multi criteria decision making methods
    Korkmazer, Cenker
    Aktar Demirtas, Ezgi
    Erol, Dogan
    [J]. PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, 2016, 22 (04): : 305 - 313
  • [35] A grey DEMATEL approach to develop third-party logistics provider selection criteria
    Govindan, Kannan
    Khodaverdi, Roohollah
    Vafadarnikjoo, Amin
    [J]. INDUSTRIAL MANAGEMENT & DATA SYSTEMS, 2016, 116 (04) : 690 - 722
  • [36] Study of Evaluation and Selection on Third Party Reverse Logistics providers
    Meng Xiangru
    [J]. ISBIM: 2008 INTERNATIONAL SEMINAR ON BUSINESS AND INFORMATION MANAGEMENT, VOL 1, 2009, : 518 - 521
  • [37] Emergency logistics centers site selection by multi-criteria decision-making and GIS
    Feng, Zengxi
    Li, Gangting
    Wang, Wenjing
    Zhang, Lutong
    Xiang, Weipeng
    He, Xin
    Zhang, Maoqiang
    Wei, Na
    [J]. INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION, 2023, 96
  • [38] A combined MCDM approach for evaluation and selection of third-party reverse logistics partner for Indian electronics industry
    Prakash, Chandra
    Barua, M. K.
    [J]. SUSTAINABLE PRODUCTION AND CONSUMPTION, 2016, 7 : 66 - 78
  • [39] Sustainable third-party reverse logistics provider evaluation and selection using fuzzy SWARA and developed fuzzy COPRAS in the presence of risk criteria
    Zarbakhshnia, Navid
    Soleimani, Hamed
    Ghaderi, Hadi
    [J]. APPLIED SOFT COMPUTING, 2018, 65 : 307 - 319
  • [40] A decision making methodology for the selection of reverse logistics operating channels
    Senthil, S.
    Srirangacharyulu, B.
    Ramesh, A.
    [J]. INTERNATIONAL CONFERENCE ON MODELLING OPTIMIZATION AND COMPUTING, 2012, 38 : 418 - 428