Supplier selection using fuzzy AHP and TOPSIS: a case study in the Indian automotive industry

被引:149
|
作者
Jain, Vipul [1 ]
Sangaiah, Arun Kumar [2 ]
Sakhuja, Sumit [3 ]
Thoduka, Nittin [3 ]
Aggarwal, Rahul [3 ]
机构
[1] Victoria Univ Wellington, Victoria Business Sch, Wellington, New Zealand
[2] VIT Univ, Sch Comp Sci & Engn, Vellore, Tamil Nadu, India
[3] GD Goennka World Inst & Lancaster Univ, Dept Mech Engn, Sohna, India
来源
NEURAL COMPUTING & APPLICATIONS | 2018年 / 29卷 / 07期
关键词
Supplier selection; AHP; TOPSIS; Consistency test; Sensitivity analysis; ANALYTIC HIERARCHY PROCESS; DECISION; SEGMENTATION;
D O I
10.1007/s00521-016-2533-z
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Supplier selection is one of the key activities of purchase management in supply chain. Supplier selection is a multifaceted problem relating qualitative and quantitative multi-criteria. This paper deals with a supplier selection problem in an Indian automobile company. The work presents selection of headlamp supplier using integrated fuzzy multi-criteria decision-making approaches: analytical hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). The selection process starts with identifying the criteria based on literature review and interviewing industry experts. Weights to criteria are assigned using AHP, and suppliers are ranked using AHP and TOPSIS. Consistency tests are carried out to check the quality of expert's inputs. Also, sensitivity analysis is done to check the robustness of the approach. The results address that fuzzy approaches could be effective and more accurate than the existing approaches for supplier selection problems.
引用
收藏
页码:555 / 564
页数:10
相关论文
共 50 条
  • [41] Strategic Decision Selection Using Hesitant fuzzy TOPSIS and Interval Type-2 Fuzzy AHP: A case study
    Sezi Cevik Onar
    Başar Oztaysi
    Cengiz Kahraman
    International Journal of Computational Intelligence Systems, 2014, 7 : 1002 - 1021
  • [42] An Industry 4.0 Technology Selection Framework for Manufacturing Systems and Firms Using Fuzzy AHP and Fuzzy TOPSIS Methods
    Pour, Parham Dadash
    Ahmed, Aser Alaa
    Nazzal, Mohammad A.
    Darras, Basil M.
    SYSTEMS, 2023, 11 (04):
  • [43] Supplier selection optimization in the automotive industry
    Tennant, C
    Sullivan, D
    QUALITY, RELIABILITY, AND MAINTENANCE, 2004, : 171 - 174
  • [44] Supplier selection in electronic marketplaces using satisficing and fuzzy AHP
    Chamodrakas, I.
    Batis, D.
    Martakos, D.
    EXPERT SYSTEMS WITH APPLICATIONS, 2010, 37 (01) : 490 - 498
  • [45] Operating system selection using fuzzy AHP and topsis methods
    Balli, Serkan
    Korukoǧlu, Serdar
    Mathematical and Computational Applications, 2009, 14 (02) : 119 - 130
  • [46] OPERATING SYSTEM SELECTION USING FUZZY AHP AND TOPSIS METHODS
    Balli, Serkan
    Korukoglu, Serdar
    MATHEMATICAL & COMPUTATIONAL APPLICATIONS, 2009, 14 (02): : 119 - 130
  • [47] Designing an integrated AHP based decision support system for supplier selection in automotive industry
    Dweiri, Fikri
    Kumar, Sameer
    Khan, Sharfuddin Ahmed
    Jain, Vipul
    EXPERT SYSTEMS WITH APPLICATIONS, 2016, 62 : 273 - 283
  • [48] Using AHP and TOPSIS approaches in nuclear power plant equipment supplier selection
    Yang Guang
    Huang Wen-Jie
    Lei Lin-li
    ADVANCED DESIGN AND MANUFACTURE II, 2010, 419-420 : 761 - +
  • [49] An Application of Fuzzy Topsis Method for Supplier Selection
    Sevkli, Mehmet
    Zaim, Selim
    Turkyilmaz, Ali
    Satir, Metin
    2010 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE 2010), 2010,
  • [50] Application of Fuzzy-TOPSIS Method in Supporting Supplier Selection with Focus on HSE Criteria: A Case Study in the Oil and Gas Industry
    Haddad, Assed N.
    da Costa, Bruno B. F.
    de Andrade, Larissa S.
    Hammad, Ahmed
    Soares, Carlos A. P.
    INFRASTRUCTURES, 2021, 6 (08)