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Supplier Selection

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 88))

Abstract

Good decision brings success, peace, and prosperity to our society. The art of decision making is the secret of all success. Extensive literature review shows that multi-criteria decision analysis (MCDA) is one of the pervasive methods which are commonly used to resolve complex and conflicting issues. In this regard, research papers are gathered from 1980 to 2012 (searched via ScienceDirect, IEEE, etc.) and out of which 73 research papers are analyzed to find salient features of analytic hierarchy process (AHP), types of scale used in AHP, modified AHP, rank reversal problem of AHP, validation of AHP, TOPSIS, normalization methods of TOPSIS, distance functions of TOPSIS, fuzzy hierarchical TOPSIS, rank reversal problem of TOPSIS, and their hybrid methods. The purpose of this chapter is to give thorough idea of MCDA tools, namely AHP, TOPSIS, VIKOR, and their hybrid methods to beginners and professionals.

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References

  • Aguarón J, Esocbar MT, Jiménez JMM (2003) Consistency stability intervals for a judgement in AHP decision support systems. Eur J Oper Res 145:382–393

    Article  MATH  Google Scholar 

  • Akhlaghi E (2011) A rough-set based approach to design an expert system for personnel selection. World Academy of Science, Engineering and Technology 78

    Google Scholar 

  • Ashtiani B, Haghighirad F, Makui A, Montazer GA (2009) Extension of fuzzy TOPSIS method based on interval-valued fuzzy sets. Appl Soft Comput 9:457–461

    Article  Google Scholar 

  • Baker D, Bridges D, Hunter R, Johnson G, Krupa J, Murphy J, Sorenson K (2002) Guidebook to decision-making methods. WSRC-IM-2002-00002, Department of Energy, USA. http://emi-web.inel.gov/Nissmg/Guidebook_2002.pdf

  • Barzilai J, Lootsma FA (1997) Power relations and group aggregation in the multiplicative AHP and SMART. J Multi-Criteria Decis Anal 6:155–165

    Article  MATH  Google Scholar 

  • Behzadian M, Otaghsara SK, Yazdani M, Ignatius J (2012) A state-of the-art survey of TOPSIS applications. Expert Syst Appl 39:13051–13069

    Google Scholar 

  • Belton V, Gear T (1982) On a shortcoming of Saaty’s method of analytic hierarchies. Omega 11(3):226–230

    Google Scholar 

  • Beynon M (2002) An analysis of distributions of priority values from alternative comparison scales within AHP. Eur J Oper Res 140:104–117

    Article  MATH  Google Scholar 

  • Cascales MSG, Lamata MT (2012) On rank reversal and TOPSIS method. Math Comput Model 56:123–132

    Article  MathSciNet  MATH  Google Scholar 

  • Chakraborty S, Yeh CH (2009) A simulation comparison of normalization procedures for TOPSIS. IEEE. ISSN: 978-1-4244-4136-5/09

    Google Scholar 

  • Chen CT (2000) Extensions of the TOPSIS for group decision making under fuzzy environment. Fuzzy Sets Syst 114:1–9

    Article  MATH  Google Scholar 

  • Chen TY, Tsao CY (2008) The interval-valued fuzzy TOPSIS method and experimental analysis. Fuzzy Sets Syst 159:1410–1428

    Article  MathSciNet  MATH  Google Scholar 

  • Choo EU, Wedley WC (2004) A common framework for deriving preference values from pair wise comparison matrices. Comput Oper Res 31:893–908

    Article  MATH  Google Scholar 

  • Chu TC, Lin YC (2009) An interval arithmetic based fuzzy TOPSIS model. Expert Syst Appl 36:10870–10876

    Article  Google Scholar 

  • Chu MT, Shyu J, Tzeng GH, Khosla R (2007) Comparison among three analytical methods for knowledge communities group-decision analysis. Expert Syst Appl 33(4):1011–1024

    Article  Google Scholar 

  • Davidrajuh R (2008) Building a Fuzzy Logic based Tool for E-readiness measurement. Electron Gov Int J 5(1):120–130

    Google Scholar 

  • De Luca A, Termini S (1972) A definition of a non-probabilistic entropy in the setting of fuzzy sets theory. Inf Control 20:201–312

    MATH  Google Scholar 

  • Dodd F, Donegan H (1995) Comparison of prioritization techniques using inter hierarchy mappings. J Oper Res Soc 46:492–498

    Article  MATH  Google Scholar 

  • Dong Y, Xu Y, Li H, Dai M (2008) A comparative study of the numerical scales and the prioritization methods in AHP. Eur J Oper Res 186:229–242

    Article  MathSciNet  MATH  Google Scholar 

  • Durbach IN, Stewart TJ (2012) Modeling uncertainty in multi-criteria decision analysis. Eur J Oper Res 223:1–14

    Article  MathSciNet  MATH  Google Scholar 

  • Govindan K, Khodaverdi R, Jafarian A (2012) A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach. J Clean Prod. doi:10.1016/j.jclepro.2012.04.014

    Google Scholar 

  • Guitouni A, Martel JM (1998) Tentative guidelines to help choosing an appropriate MCDA method. Eur J Oper Res 109:501–521

    Article  MATH  Google Scholar 

  • Guo Z, Zhang Y (2010) The third-party logistics performance evaluation based on the AHP-PCA model. IEEE. ISBN:978-1-4244-7161-4/10

    Google Scholar 

  • Guo CG, Liu YX, Hou SM, Wang W (2010) Innovative product design based on customer requirement weight calculation model. Int J Autom Comput 7(4):578–583. doi:10.1007/s11633-010-0543-3

    Article  Google Scholar 

  • Harker P, Vargas L (1987) The theory of ratio scale estimation: Saaty’s analytic hierarchy process. Manage Sci 33:1383–1403

    Article  MathSciNet  Google Scholar 

  • Hwang CL, Yoon K (1981) Multiple attribute decision making. Springer-Verlag, Berlin

    Book  MATH  Google Scholar 

  • Ishizaka A, Labib A (2011) Review of the main developments in the analytic hierarchy process. Expert Syst Appl 38:14336–14345

    Article  Google Scholar 

  • Ishizaka A, Balkenborg D, Kaplan T (2010) Influence of aggregation and measurement scale on ranking a compromise alternative in AHP. J Oper Res Soc 62:700–710

    Article  Google Scholar 

  • May EC, Spottiswoode SJP, James, CL (1994) Shannon entropy: a possible intrinsic target property. J Parapsychology 58

    Google Scholar 

  • Jousselme A-L, Liu C, Grnecier D, Bossé Ẻ (2005) Measuring ambiguity in the evidence theory. IEEE Trans Syst Man Cybern Part A Syst Hum. doi:10.1109/TSMCA.2005.853483

  • Jr JT, Delhaye C, Kunsch PL (1989) An interactive decision support system (IDSS) for multicriteria decision aid. Math Comput Model 12(10/11):131l–1320

    Google Scholar 

  • Leung LC, Cao D (2001) On the efficacy of modeling multi-attribute decision problems using AHP and Sinarchy. Eur J Oper Res 132:39–49

    Article  MathSciNet  MATH  Google Scholar 

  • Li TS, Huang HH (2009) Applying TRIZ and Fuzzy AHP to develop innovative design for automated manufacturing systems. Expert Syst Appl 36:8302–8312

    Article  Google Scholar 

  • Lilly DP, Cory J, Hissem B (2009) The use of principal component analysis to integrate blasting into the mining process. In: Proceedings of 2009 Oxford Business & Economics Conference Program. ISBN: 978-09742114-1-9

    Google Scholar 

  • Lin MC, Wang CC, Chen MS, Chang CA (2008) Using AHP and TOPSIS approaches in customer-driven product design process. Comput Ind 59:17–31

    Article  Google Scholar 

  • Liu P, Wang M (2011) An extended VIKOR method for multiple attribute group decision making based on generalized interval-valued trapezoidal fuzzy numbers. Sci Res Essays 6(4):766–776

    Google Scholar 

  • Lootsma F (1989) Conflict resolution via pair-wise comparison of concessions. Eur J Oper Res 40:109–116

    Article  MathSciNet  Google Scholar 

  • Ma D, Zheng X (1991) 9/9-9/1 Scale method of AHP. In: Proceedings of Second International Symposium on AHP, Pittsburgh

    Google Scholar 

  • Najmi A, Makui A (2010) Providing hierarchical approach for measuring supply chain performance using AHP and DEMATEL methodologies. Int J Ind Eng Comput 1:199–212

    Google Scholar 

  • Nezhad SS, Damghani KK (2009) Application of a fuzzy TOPSIS method base on modified preference ratio and fuzzy distance measurement in assessment of traffic police centers performance. Appl Soft Comput. doi:10.1016/j.asoc.2009.08.036

    Google Scholar 

  • Olson DL (2004) Comparison of weights in TOPSIS Models. Math Comput Model 40:721–727

    Article  MathSciNet  MATH  Google Scholar 

  • Opricovic S (1998) Multicriteria optimization of civil engineering systems. Faculty of Civil Engineering, Belgrade

    Google Scholar 

  • Opricovic S, Tzeng GH (2004) Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur J Oper Res 156:445–455

    Article  MATH  Google Scholar 

  • Opricovic S, Tzeng GH (2007) Extended VIKOR method in comparison with outranking methods. Eur J Oper Res 178(2):514–529

    Article  MATH  Google Scholar 

  • Parkan C, Wu ML (1997) On the equivalence of operational performance measurement and multiple attribute decision making. Int J Prod Res 35(11):2963–2988

    Article  MATH  Google Scholar 

  • Qureshi ME, Harrison SR, Wegener MK (1999) Validation of multicriteria analysis models. Agric Syst 62:105–116

    Article  Google Scholar 

  • Rosenbloom ES (1996) A probabilistic interpretation of the final rankings in AHP. Eur J Oper Res 96:371–378

    Article  MATH  Google Scholar 

  • Ross TJ (2007) Fuzzy logic with engineering applications. Wiley India Edition

    Google Scholar 

  • Roy B (1985) Mèthodologie Multicritère D’Aide à la Dècision. Ćollection Gestion—Edition Economica, Paris

    Google Scholar 

  • Saaty T (1977) A scaling method for priorities in hierarchical structures’. J Math Psychol 15(3):234–281

    Article  MathSciNet  MATH  Google Scholar 

  • Saaty TL (1990) Eigenvector and logarithmic least squares. Eur J Oper Res 48:156–160

    Article  MATH  Google Scholar 

  • Saaty TL (1994) Highlights and critical points in the theory and application of the analytic hierarchy process. Eur J Oper Res 74:426–447

    Article  MATH  Google Scholar 

  • Saaty TL (2004) Decision making—the analytic hierarchy and network process (AHP/ANP). J Syst Sci Syst Eng 13(1):1–34

    Article  MathSciNet  Google Scholar 

  • Saaty TL, Shih HS (2009) Structures in decision making: on the subjective geometry of hierarchies and networks. Eur J Oper Res 199:867–872

    Article  MathSciNet  MATH  Google Scholar 

  • Saaty TL, Vargas LG (1984) The legitimacy of rank reversal. OMEGA Int J Manag Sci 12(5):513–516

    Article  Google Scholar 

  • Saghafian S, Hejazi SR (2005) Multi-criteria group decision making using a modified fuzzy TOPSIS procedure. In: Proceeding 2005 International Conference on Computational Intelligence for Modelling, Control and Automation, and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC’05). ISSN 0-7695-2504-0/05

    Google Scholar 

  • Salo A, Hamalainen R (1997) On the measurement of preference in the analytic hierarchy process. J Multi-Criteria Decis Anal 6:309–319

    Article  MATH  Google Scholar 

  • Schoner B, Wedley WC (1989) Ambiguous criteria weights in AHP: consequences and solutions. Decis Sci 20:462–475

    Article  Google Scholar 

  • Schoner B, Choo EU, Wedley WC (1997) A comment on ‘rank disagreement: a comparison of multi-criteria methodologies’. J Multi-Criteria Decis Anal 6:197–200

    Article  MATH  Google Scholar 

  • Shih HS, Shyur HJ, Lee ES (2007) An extension of TOPSIS for group decision making. Math Comput Model 45:801–813

    Article  MATH  Google Scholar 

  • Shim JP (1989) Bibliographical research on the analytic hierarchy process (AHP). Socio-Econ Plann Sci 23(3):161–167

    Article  MathSciNet  Google Scholar 

  • Srdjevic B (2005) Combining different prioritization methods in the analytic hierarchy process synthesis. Comput Oper Res 32:1897–1919

    Article  MATH  Google Scholar 

  • Subramanian N, Ramanathan R (2012) A review of applications of analytic hierarchy process in operations management. Int J Prod Econ 138:215–241

    Article  Google Scholar 

  • Szmidt E, Kacprzyk J ( 2000) Distance between intuitionistic fuzzy sets. Fuzzy Sets System 114(3):505–518

    Google Scholar 

  • Taha HA (2006) Operations research—an introduction. Prentice-Hall of India Pvt, Ltd

    MATH  Google Scholar 

  • Taleizadeh AA, Niaki STA, Aryanezhad MB (2009) A hybrid method of Pareto, TOPSIS and genetic algorithm to optimize multi-product multi-constraint inventory control systems with random fuzzy replenishments. Math Comput Model 49:1044–1057

    Article  MathSciNet  MATH  Google Scholar 

  • Tolga E, Demircan ML, Kahraman C (2005) Operating system selection using fuzzy replacement analysis and analytic hierarchy process. Int J Prod Econ 97:89–117

    Google Scholar 

  • Tsou CS (2008) Multi-objective inventory planning using MOPSO and TOPSIS. Expert Syst Appl 35:136–142

    Article  Google Scholar 

  • Vaidya OS, Kumar S (2006) Analytic hierarchy process: An overview of applications. Eur J Oper Res 169:1–29

    Article  MathSciNet  MATH  Google Scholar 

  • Wang YM, Elhag TMS (2006) An approach to avoiding rank reversal in AHP. Decis Support Syst 42:1474–1480

    Article  Google Scholar 

  • Wang YJ, Lee HS (2007) Generalizing TOPSIS for fuzzy multiple-criteria group decision-making. Comput Math Appl 53:1762–1772

    Article  MathSciNet  MATH  Google Scholar 

  • Wang TC, Lee HD (2009) Developing a fuzzy TOPSIS approach based on subjective weights and objective weights. Expert Syst Appl 36:8980–8985

    Article  Google Scholar 

  • Wang JW, Cheng CH, Cheng HK (2008) Fuzzy hierarchical TOPSIS for supplier selection. Appl Soft Comput. doi:10.1016/j.asoc.2008.04.014

    Google Scholar 

  • Whitaker R (2007) Validation examples of the analytic hierarchy process and analytic network process. Math Comput Model 46:840–859

    Article  MathSciNet  MATH  Google Scholar 

  • Xia W, Wu Z (2007) Supplier selection with multiple criteria in volume discount Environments. Omega 35:494–504

    Article  Google Scholar 

  • Yager RR (1979) On the measure of fuzziness and negation Part 1: membership in unit interval. Int J Gen Syst 5:21–229

    Article  Google Scholar 

  • Zadeh AA, Izadbaksh HR (2008) A multi-variate/ multi-attribute approach for plant layout design. Int J Ind Eng 15(2):143–154

    Google Scholar 

  • Zanakis SH, Solomon A, Wishart N, Dublish S (1998) Multi-attribute decision making: a simulation comparison of selection methods. Eur J Oper Res 107:507–529

    Article  MATH  Google Scholar 

  • Zeleny M (1974) A concept of compromise solutions and the method of the displaced ideal. Comput Oper Res 1:479–496

    Article  Google Scholar 

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Correspondence to Krishnendu Mukherjee .

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Mukherjee, K. (2017). Overview. In: Supplier Selection. Studies in Systems, Decision and Control, vol 88. Springer, New Delhi. https://doi.org/10.1007/978-81-322-3700-6_1

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  • DOI: https://doi.org/10.1007/978-81-322-3700-6_1

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