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Published in: Granular Computing 4/2020

22-05-2019 | Original Paper

Supplier selection using a flexible interval-valued fuzzy VIKOR

Author: Iman Mohamad Sharaf

Published in: Granular Computing | Issue 4/2020

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Abstract

One of the major issues in a supply chain (SC) is the selection of the appropriate supplier. Supplier selection (SS) plays a vital role in achieving an effective and successful SC, hence gaining a competitive advantage. This article proposes a novel flexible multi-attribute group decision-making method for SS based on VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) using interval-valued fuzzy sets (IVFSs). The method avoids defuzzification, minimizes the computations, and considers the decision-makers’ optimism level. Avoiding defuzzification keeps the characteristics of (IVFSs) and prevents the loss of information. To minimize the computations, two main modifications are done. While all VIKOR-based techniques use both the best and the worst solutions; the proposed VIKOR uses the best solution only, and the division operations by the difference between two fuzzy sets to compute the separation measures and the index Q are eliminated. Ranking plays a crucial role in VIKOR, since three ranking lists are required. The signed distance is modified and used for ranking due to its simple, few computations. None of the previously VIKOR-based techniques accounted for the decision-makers’ optimism level. Therefore, the signed distance is used in its basic form to keep the α-level explicitly in the ranking formula. Thus, the proposed technique preserves fuzziness, reduces the computations substantially, and allows the participation of the decision-makers through the optimism level. Two examples are solved: one for illustration and the other to compare the results with previously used methods.

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Literature
go back to reference Adeinat H, Ventura JA (2018) Integrated pricing and supplier selection in a two-stage supply chain. Int J Prod Econ 201:193–202MATH Adeinat H, Ventura JA (2018) Integrated pricing and supplier selection in a two-stage supply chain. Int J Prod Econ 201:193–202MATH
go back to reference Chan FTS, Kumar N (2007) Global supplier development considering risk factors using fuzzy extended AHP-based approach. Omega 35:417–431 Chan FTS, Kumar N (2007) Global supplier development considering risk factors using fuzzy extended AHP-based approach. Omega 35:417–431
go back to reference Chatterjee K, Kar S (2017) Unified granular-number-based AHP-VIKOR multi-criteria decision framework. Granul Comput 2:199–221 Chatterjee K, Kar S (2017) Unified granular-number-based AHP-VIKOR multi-criteria decision framework. Granul Comput 2:199–221
go back to reference Chen C-T (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114:1–9MATH Chen C-T (2000) Extensions of the TOPSIS for group decision-making under fuzzy environment. Fuzzy Sets Syst 114:1–9MATH
go back to reference Chen T-Y (2012) Multiple criteria group decision-making with generalized interval-valued fuzzy numbers based on signed distances and incomplete weights. Appl Math Model 36:3029–3052MathSciNetMATH Chen T-Y (2012) Multiple criteria group decision-making with generalized interval-valued fuzzy numbers based on signed distances and incomplete weights. Appl Math Model 36:3029–3052MathSciNetMATH
go back to reference Chen S-M, Chang Y-C (2011) Weighted fuzzy rule interpolation based on GA-based weight-learning techniques. IEEE Trans Fuzzy Syst 19(4):729–744MathSciNet Chen S-M, Chang Y-C (2011) Weighted fuzzy rule interpolation based on GA-based weight-learning techniques. IEEE Trans Fuzzy Syst 19(4):729–744MathSciNet
go back to reference Chen S-M, Hsiao W-H (2000) Bidirectional approximate reasoning for rule-based systems using interval-valued fuzzy sets. Fuzzy Sets Syst 113:185–203MathSciNetMATH Chen S-M, Hsiao W-H (2000) Bidirectional approximate reasoning for rule-based systems using interval-valued fuzzy sets. Fuzzy Sets Syst 113:185–203MathSciNetMATH
go back to reference Chen S-M, Huang C-M (2003) Generating weighted fuzzy rules from relational database systems for estimating null values using genetic algorithms. IEEE Trans Fuzzy Syst 11(4):495–506 Chen S-M, Huang C-M (2003) Generating weighted fuzzy rules from relational database systems for estimating null values using genetic algorithms. IEEE Trans Fuzzy Syst 11(4):495–506
go back to reference Chen S-M, Tanuwijaya K (2011) Fuzzy forecasting based on high-order fuzzy logical relationships and automatic clustering techniques. Expert Syst Appl 38(2011):15425–15437 Chen S-M, Tanuwijaya K (2011) Fuzzy forecasting based on high-order fuzzy logical relationships and automatic clustering techniques. Expert Syst Appl 38(2011):15425–15437
go back to reference Chen S-M, Hsiao W-H, Jong W-T (1997) Bidirectional approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets Syst 91(3):339–353MathSciNetMATH Chen S-M, Hsiao W-H, Jong W-T (1997) Bidirectional approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets Syst 91(3):339–353MathSciNetMATH
go back to reference Chen S-M, Chang Y-C, Pan J-S (2012a) Fuzzy rules interpolation for sparse fuzzy rule-based systems based on interval type-2 Gaussian fuzzy sets and genetic algorithms. IEEE Trans Fuzzy Syst 21(3):412–425 Chen S-M, Chang Y-C, Pan J-S (2012a) Fuzzy rules interpolation for sparse fuzzy rule-based systems based on interval type-2 Gaussian fuzzy sets and genetic algorithms. IEEE Trans Fuzzy Syst 21(3):412–425
go back to reference Chen S-M, Chu H-P, Sheu T-W (2012b) TAIEX forecasting using fuzzy time series and automatically generated weights of multiple factors. IEEE Trans Syst Man Cybern Part A Syst Hum 42(6):1485–1495 Chen S-M, Chu H-P, Sheu T-W (2012b) TAIEX forecasting using fuzzy time series and automatically generated weights of multiple factors. IEEE Trans Syst Man Cybern Part A Syst Hum 42(6):1485–1495
go back to reference Chen S-M, Manalu GMT, Pan J-S, Liu H-C (2013) Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization techniques. IEEE Trans Cybern 43(3):1102–1117 Chen S-M, Manalu GMT, Pan J-S, Liu H-C (2013) Fuzzy forecasting based on two-factors second-order fuzzy-trend logical relationship groups and particle swarm optimization techniques. IEEE Trans Cybern 43(3):1102–1117
go back to reference Cheng S-H, Chen S-M, Jian W-S (2016) Fuzzy time series forecasting based on fuzzy logical relationships and similarity measures. Inf Sci 327:272–287MathSciNetMATH Cheng S-H, Chen S-M, Jian W-S (2016) Fuzzy time series forecasting based on fuzzy logical relationships and similarity measures. Inf Sci 327:272–287MathSciNetMATH
go back to reference Chiang J (2001) Fuzzy linear programming based on statistical confidence interval and interval-valued fuzzy set. Eur J Oper Res 129(1):65–86MathSciNetMATH Chiang J (2001) Fuzzy linear programming based on statistical confidence interval and interval-valued fuzzy set. Eur J Oper Res 129(1):65–86MathSciNetMATH
go back to reference Dickson GW (1996) An analysis of vendor selection systems and decisions. J Purch 2(1):5–17 Dickson GW (1996) An analysis of vendor selection systems and decisions. J Purch 2(1):5–17
go back to reference Dymova L, Sevastjanov P, Tikhonenko A (2015) An interval type-2 fuzzy extension of the TOPSIS methods using alpha cuts. Knowl Based Syst 83:116–127 Dymova L, Sevastjanov P, Tikhonenko A (2015) An interval type-2 fuzzy extension of the TOPSIS methods using alpha cuts. Knowl Based Syst 83:116–127
go back to reference Figueroa-Garcia JC, Chalco-Cano YC, Roman-Florez H (2015) Distance measures for interval-type-2 fuzzy numbers. Discrete Appl Math 197:93–102MathSciNetMATH Figueroa-Garcia JC, Chalco-Cano YC, Roman-Florez H (2015) Distance measures for interval-type-2 fuzzy numbers. Discrete Appl Math 197:93–102MathSciNetMATH
go back to reference Ghorabaee MK (2016) Developing an MCDM method for robot selection with interval type-2 fuzzy sets. Robot Comput Integr Manuf 37:221–232 Ghorabaee MK (2016) Developing an MCDM method for robot selection with interval type-2 fuzzy sets. Robot Comput Integr Manuf 37:221–232
go back to reference Gorzalczany MB (1987) A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets Syst 21:1–17MathSciNetMATH Gorzalczany MB (1987) A method of inference in approximate reasoning based on interval-valued fuzzy sets. Fuzzy Sets Syst 21:1–17MathSciNetMATH
go back to reference Gul M, Celik E, Aydin N, Gumus AT, Guneri AF (2016) A state of the art literature review of VIKOR and its fuzzy extensions on applications. Appl Soft Comput 46:60–89 Gul M, Celik E, Aydin N, Gumus AT, Guneri AF (2016) A state of the art literature review of VIKOR and its fuzzy extensions on applications. Appl Soft Comput 46:60–89
go back to reference Heiderzade A, Mahdavi I, Mahdavi-Amiri N (2016) Supplier selection using a clustering method based on a new distance for interval type-2 fuzzy sets: a case study. Appl Soft Comput 38:213–231 Heiderzade A, Mahdavi I, Mahdavi-Amiri N (2016) Supplier selection using a clustering method based on a new distance for interval type-2 fuzzy sets: a case study. Appl Soft Comput 38:213–231
go back to reference Hsu HM, Chen CT (1997) Fuzzy credibility relation method for multiple criteria decision-making problems. Inf Sci 96:79–91MATH Hsu HM, Chen CT (1997) Fuzzy credibility relation method for multiple criteria decision-making problems. Inf Sci 96:79–91MATH
go back to reference Ju Y, Wang A (2013) Extension of VIKOR method for multi-criteria group decision-making problem with linguistic information. Appl Math Model 37:3112–3125MathSciNetMATH Ju Y, Wang A (2013) Extension of VIKOR method for multi-criteria group decision-making problem with linguistic information. Appl Math Model 37:3112–3125MathSciNetMATH
go back to reference Kohout LJ, Bandler W (1996) Fuzzy interval inference utilizing the checklist paradigm and BK-relational products. In: Kearfort RB et al (eds) Applications of interval computations. Kluwer, Dordrecht, pp 291–335MATH Kohout LJ, Bandler W (1996) Fuzzy interval inference utilizing the checklist paradigm and BK-relational products. In: Kearfort RB et al (eds) Applications of interval computations. Kluwer, Dordrecht, pp 291–335MATH
go back to reference Kumar GK, Rao MS, Kesava Rao VVS (2018) Supplier selection and order allocation in supply chain. Mater Today Proc 5(5):12161–12173 Kumar GK, Rao MS, Kesava Rao VVS (2018) Supplier selection and order allocation in supply chain. Mater Today Proc 5(5):12161–12173
go back to reference Lee L-W, Chen S-M (2008) Fuzzy risk analysis based on fuzzy numbers with different shapes and different deviations. Expert Syst Appl 34:2763–2771 Lee L-W, Chen S-M (2008) Fuzzy risk analysis based on fuzzy numbers with different shapes and different deviations. Expert Syst Appl 34:2763–2771
go back to reference Liang Q, Mendel J (2000) Interval-type 2 fuzzy logic systems: theory and design. IEEE Trans Fuzzy Syst 8(5):535–550 Liang Q, Mendel J (2000) Interval-type 2 fuzzy logic systems: theory and design. IEEE Trans Fuzzy Syst 8(5):535–550
go back to reference Lima Junior FR, Osiro L, Carpinetti LCR (2014) A comparison between fuzzy AHP and fuzzy TOPSIS methods to supplier selection. Appl Soft Comput 21:194–209 Lima Junior FR, Osiro L, Carpinetti LCR (2014) A comparison between fuzzy AHP and fuzzy TOPSIS methods to supplier selection. Appl Soft Comput 21:194–209
go back to reference Liu J, Liang Y (2017) Multi-granularity unbalanced linguistic group decision-making with incomplete weight information based on VIKOR method. Granul Comput 3(3):219–228 Liu J, Liang Y (2017) Multi-granularity unbalanced linguistic group decision-making with incomplete weight information based on VIKOR method. Granul Comput 3(3):219–228
go back to reference Liu K, Liu Y, Qin J (2018a) An integrated ANP-VIKOR methodology for supplier selection with interval type-2 fuzzy sets. Granul Comput 3(3):193–208 Liu K, Liu Y, Qin J (2018a) An integrated ANP-VIKOR methodology for supplier selection with interval type-2 fuzzy sets. Granul Comput 3(3):193–208
go back to reference Liu S, Xu Z, Gao J (2018b) A fuzzy compromise programming model based on the modified S-curve membership functions for supplier selection. Granul Comput 3(4):275–283 Liu S, Xu Z, Gao J (2018b) A fuzzy compromise programming model based on the modified S-curve membership functions for supplier selection. Granul Comput 3(4):275–283
go back to reference Mavi RK, Goh M, Mavi NK (2016) Supplier selection with Shannon entropy and fuzzy TOPSIS context of supply chain risk management. In: 12th International strategic conference, ISMC 2016, October 2016, Antalya, Turkey Mavi RK, Goh M, Mavi NK (2016) Supplier selection with Shannon entropy and fuzzy TOPSIS context of supply chain risk management. In: 12th International strategic conference, ISMC 2016, October 2016, Antalya, Turkey
go back to reference Mehbodniya A, Kaleem F, Yen KK, Adachi F (2013) A fuzzy extension of VIKOR for target network selection in heterogeneous wireless environments. Phys Commun 7:145–155 Mehbodniya A, Kaleem F, Yen KK, Adachi F (2013) A fuzzy extension of VIKOR for target network selection in heterogeneous wireless environments. Phys Commun 7:145–155
go back to reference Mendel JM (2016) A comparison of three approaches for estimating (synthesizing) an interval type-2 fuzzy set model of linguistic term for computing with words. Granul Comput 1:59–69 Mendel JM (2016) A comparison of three approaches for estimating (synthesizing) an interval type-2 fuzzy set model of linguistic term for computing with words. Granul Comput 1:59–69
go back to reference Niewiadomski A (2007) Interval-Valued and Interval Type-2 Fuzzy Sets: A Subjective Comparison. IEEE International Fuzzy Systems Conference. IEEE, London, UK Niewiadomski A (2007) Interval-Valued and Interval Type-2 Fuzzy Sets: A Subjective Comparison. IEEE International Fuzzy Systems Conference. IEEE, London, UK
go back to reference Nilashi M, Ibrahim O, Ahmadi H, Shahmoradi L (2017) A knowledge-based system for breast cancer classification using fuzzy logic method. Telemat Inform 34(4):133–144 Nilashi M, Ibrahim O, Ahmadi H, Shahmoradi L (2017) A knowledge-based system for breast cancer classification using fuzzy logic method. Telemat Inform 34(4):133–144
go back to reference Opricovic S (1998) Multicriteria optimization of civil engineering systems. Faculty of Civil Engineering, Belgrade Opricovic S (1998) Multicriteria optimization of civil engineering systems. Faculty of Civil Engineering, Belgrade
go back to reference Opricovic S (2011) Fuzzy VIKOR with an application to water resources planning. Expert Syst Appl 38:12983–12990 Opricovic S (2011) Fuzzy VIKOR with an application to water resources planning. Expert Syst Appl 38:12983–12990
go back to reference Opricovic S, Tzeng G-H (2004) Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur J Oper Res 156:445–455MATH Opricovic S, Tzeng G-H (2004) Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur J Oper Res 156:445–455MATH
go back to reference Ordoobadi SM (2009) Development of a supplier selection model using fuzzy logic. Supply Chain Manag Int J 14(4):314–327 Ordoobadi SM (2009) Development of a supplier selection model using fuzzy logic. Supply Chain Manag Int J 14(4):314–327
go back to reference Pedrycz W (1991) Fuzzy logic in development of fundamentals of pattern recognition. Int J Approx Reason 5(3):251–264MATH Pedrycz W (1991) Fuzzy logic in development of fundamentals of pattern recognition. Int J Approx Reason 5(3):251–264MATH
go back to reference Ploskas N, Papathanasiou J, Tsaples G (2017) Implementation of an extended fuzzy VIKOR method based on triangular and trapezoidal fuzzy linguistic variables and alternative defuzzification techniques. In: Linden I, Liu S, Colot C (eds) Decision support systems VII. Data, Information and Knowledge Visualization in Decision Support Systems. ICDSST 2017. Lecture Notes in Business Information Processing. Springer, Cham, vol 282, pp 165–178 Ploskas N, Papathanasiou J, Tsaples G (2017) Implementation of an extended fuzzy VIKOR method based on triangular and trapezoidal fuzzy linguistic variables and alternative defuzzification techniques. In: Linden I, Liu S, Colot C (eds) Decision support systems VII. Data, Information and Knowledge Visualization in Decision Support Systems. ICDSST 2017. Lecture Notes in Business Information Processing. Springer, Cham, vol 282, pp 165–178
go back to reference Rashid T, Beg I, Husnine SM (2014) Robot selection by using generalized interval-valued fuzzy numbers with TOPSIS. Appl Soft Comput 21:462–468 Rashid T, Beg I, Husnine SM (2014) Robot selection by using generalized interval-valued fuzzy numbers with TOPSIS. Appl Soft Comput 21:462–468
go back to reference Sanayei A, Farid SM, Yazdankhah A (2010) Group decision-making process for supplier selection with VIKOR under fuzzy environment. Expert Syst Appl 37(1):24–30 Sanayei A, Farid SM, Yazdankhah A (2010) Group decision-making process for supplier selection with VIKOR under fuzzy environment. Expert Syst Appl 37(1):24–30
go back to reference Sari K (2017) A novel multi-criteria decision framework for evaluating green supply chain management practices. Comput Ind Eng 105:338–347 Sari K (2017) A novel multi-criteria decision framework for evaluating green supply chain management practices. Comput Ind Eng 105:338–347
go back to reference Sayadi MK, Heydari M, Shahanaghi K (2009) Extension of VIKOR method for decision- making problem with interval numbers. Appl Math Model 33:2257–2262MathSciNetMATH Sayadi MK, Heydari M, Shahanaghi K (2009) Extension of VIKOR method for decision- making problem with interval numbers. Appl Math Model 33:2257–2262MathSciNetMATH
go back to reference Shemshadi A, Shirazi H, Toreihi M, Tarokh MJ (2011) A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Syst Appl 38:12160–12167 Shemshadi A, Shirazi H, Toreihi M, Tarokh MJ (2011) A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting. Expert Syst Appl 38:12160–12167
go back to reference Shureshjani RA, Darehmiraki M (2013) A new parametric method for ranking fuzzy numbers. Indag Math 24:518–529MathSciNetMATH Shureshjani RA, Darehmiraki M (2013) A new parametric method for ranking fuzzy numbers. Indag Math 24:518–529MathSciNetMATH
go back to reference Sola HB, Fernandez J, Hagras H, Herrera F, Pagola M, Barrenechea E (2015) Interval type 2fuzzy sets: toward a wider view on their relationship. IEEE Trans Fuzzy Syst 23(5):1876–1882 Sola HB, Fernandez J, Hagras H, Herrera F, Pagola M, Barrenechea E (2015) Interval type 2fuzzy sets: toward a wider view on their relationship. IEEE Trans Fuzzy Syst 23(5):1876–1882
go back to reference Stevenson WJ (2005) Operations management, 8th edn. McGraw Hill, New York Stevenson WJ (2005) Operations management, 8th edn. McGraw Hill, New York
go back to reference Sumbac R (1975) Function Φ-Flous, Application a l’aide au diagnostic en pathologie thyroidienne. Thèse de Doctorate en Medicine, Séction Medecine University of Marseille, Marseille, France Sumbac R (1975) Function Φ-Flous, Application a l’aide au diagnostic en pathologie thyroidienne. Thèse de Doctorate en Medicine, Séction Medecine University of Marseille, Marseille, France
go back to reference Türk S, John R, Özcan E (2014) Interval type-2 fuzzy sets in supplier selection. In: 14th UK workshop on computational intelligence (UKCI), Bradford, UK 8–10 Sept. 2014 Türk S, John R, Özcan E (2014) Interval type-2 fuzzy sets in supplier selection. In: 14th UK workshop on computational intelligence (UKCI), Bradford, UK 8–10 Sept. 2014
go back to reference Türkşen IB (1986) Interval-valued strict sets based on normal forms. Fuzzy Sets Syst 20:183–195 Türkşen IB (1986) Interval-valued strict sets based on normal forms. Fuzzy Sets Syst 20:183–195
go back to reference Türkşen IB (1996) Interval-valued strict preference with Zadeh triples. Fuzzy Sets Syst 20:191–210MathSciNetMATH Türkşen IB (1996) Interval-valued strict preference with Zadeh triples. Fuzzy Sets Syst 20:191–210MathSciNetMATH
go back to reference Vahdani B, Hadipour H, Sadaghiani JS, Amiri M (2010) Extension of VIKOR method based on interval-valued fuzzy sets. Int Adv Manuf Technol 47:1231–1239 Vahdani B, Hadipour H, Sadaghiani JS, Amiri M (2010) Extension of VIKOR method based on interval-valued fuzzy sets. Int Adv Manuf Technol 47:1231–1239
go back to reference Van Laarhoven PJM, Pedrycz W (1983) A fuzzy extension of Saaty’s priority theory. Fuzzy Sets Syst 11:229–241MathSciNetMATH Van Laarhoven PJM, Pedrycz W (1983) A fuzzy extension of Saaty’s priority theory. Fuzzy Sets Syst 11:229–241MathSciNetMATH
go back to reference Yazdani M, Graeml FR (2014) VIKOR and its applications: a state-of-the-art survey. Int J Strateg Decis Sci 5(2):56–83 Yazdani M, Graeml FR (2014) VIKOR and its applications: a state-of-the-art survey. Int J Strateg Decis Sci 5(2):56–83
go back to reference Zadeh LH (1975) The concept of a linguistic variable and its applications to approximate reasoning. Inf Sci 8:199–249MathSciNetMATH Zadeh LH (1975) The concept of a linguistic variable and its applications to approximate reasoning. Inf Sci 8:199–249MathSciNetMATH
go back to reference Zhang H, Zhang W, Mei C (2009) Entropy of interval-valued fuzzy sets based on distance and its relationship with similarity measure. Knowl Based Syst 22:449–454 Zhang H, Zhang W, Mei C (2009) Entropy of interval-valued fuzzy sets based on distance and its relationship with similarity measure. Knowl Based Syst 22:449–454
Metadata
Title
Supplier selection using a flexible interval-valued fuzzy VIKOR
Author
Iman Mohamad Sharaf
Publication date
22-05-2019
Publisher
Springer International Publishing
Published in
Granular Computing / Issue 4/2020
Print ISSN: 2364-4966
Electronic ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-019-00169-3

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