A trapezoidal type-2 fuzzy multi-criteria decision making method based on TOPSIS for supplier selection: An application in textile sector
Tedarikçi seçimi için TOPSIS tabanlı ikizkenar yamuk tip-2 bulanık çok kriterli karar verme metodu: Tekstil sektöründe bir uygulama

Berk Ayvaz [1] , Ali Osman Kuşakcı [2]

163 137

Supplier evaluation and selection includes both qualitative and quantitative criteria and it is considered as a complex Multi Criteria Decision Making (MCDM) problem. Uncertainty and impreciseness of data is an integral part of decision making process for a real life application. The fuzzy set theory allows making decisions under uncertain environment. In this paper, a trapezoidal type 2 fuzzy multi-criteria decision making methods based on TOPSIS is proposed to select convenient supplier under vague information. The proposed method is applied to the supplier selection process of a textile firm in Turkey. In addition, the same problem is solved with type 1 fuzzy TOPSIS to confirm the findings of type 2 fuzzy TOPSIS. A sensitivity analysis is conducted to observe how the decision changes under different scenarios. Results show that the presented type 2 fuzzy TOPSIS method is more appropriate and effective to handle the supplier selection in uncertain environment.

Tedarikçi değerlendirme ve seçimi, nitel ve nicel çok sayıda faktörün değerlendirilmesini gerektiren karmaşık birçok kriterli karar verme problemi olarak görülmektedir. Gerçek hayatta, belirsizlikler ve muğlaklık bir karar verme sürecinin ayrılmaz bir parçası olarak karşımıza çıkmaktadır. Bulanık küme teorisi, belirsizlik durumunda karar vermemize imkân sağlayan metotlardan bir tanesidir. Bu çalışmada, ikizkenar yamuk tip 2 bulanık TOPSIS yöntemi kısaca tanıtılmıştır. Tanıtılan yöntem, Türkiye’de bir tekstil firmasının tedarikçi seçimi problemine uygulanmıştır. Ayrıca, tip 2 bulanık TOPSIS yönteminin sonuçlarını desteklemek için aynı problem tip 1 bulanık TOPSIS ile de çözülmüştür. Duyarlılık analizi yapılarak önerilen çözümler farklı senaryolar altında incelenmiştir. Duyarlılık analizi sonuçlarına göre tip 2 bulanık TOPSIS daha efektif ve uygun çözümler üretmektedir.

  • Kannan D, Khodaverdi R, Olfat L, Jafarian A, Diabat A. “Integrated fuzzy multi criteria decision making method and multiobjective programming approach for supplier selection and order allocation in a green supply chain”. Journal of Cleaner Production, 47, 355-367, 2013.
  • Liao CN. “Applying fuzzy-MSGP approach for supplier evaluation and selection in food industry”. African Journal of Agricultural Research, 7(5), 726-740, 2012.
  • Zeydan M, Çolpan C, Çobanoğlu C. “A combined methodology for supplier selection and performance evaluation”. Expert Systems with Applications, 38(3),2741-2751, 2011.
  • Shemshadi A, Shirazi H, Toreihi M, Tarokh MJ. “A fuzzy VIKOR method for supplier selection based on entropy measure for objective weighting”. Expert Systems with Applications, 38(10), 12160-12167, 2011.
  • Scott J, Ho W, Dey PK, Talluri S. “A decision support system for supplier selection and order allocation in stochastic, multi-stakeholder and multi-criteria environments”. Interational Journal of Productions Economics, 166, 226-237, 2014.
  • Rajesh R, Ravi V. “Supplier selection in resilient supply chains : a grey relational analysis approach”. Journal of Cleaner Production, 86, 343-359, 2015.
  • Chen CT. “Extensions of the TOPSIS for group decision-making under fuzzy environment”. Fuzzy Sets Systems, 114(1), 1-9, 2000.
  • Dereli T, Altun K. “Technology evaluation through the use of interval type-2 fuzzy sets and systems”. Computers & Industrial Engineering, 65(4), 624-633, 2013.
  • Xu ZS, Chen J. “An interactive method for fuzzy multiple attribute group decision making”. Information Sciences, 177(1), 248-263, 2007.
  • Kahraman C, Öztayşi B, Sarı İ U, Turanoğlu E. “Fuzzy analytic hierarchy process with interval type-2 fuzzy sets”. Knowledge-Based Systems, 59, 48-57, 2014.
  • Zadeh LA. “Fuzzy sets”. Information and Control, 8, 338-353, 1965.
  • Temur G, Kaya T, Kahraman C. Facility Location Selection in Reverse Logistics Using a Type-2 Fuzzy Decision aid Method. In C. Editors: Kahraman C, Oztaysi B. Supply Chain Management Under Fuzziness. Studies in Fuzziness and Soft Computing, 591-606, Berlin, Germany, Springer, 2014.
  • Zhang Z, Zhang S. “A novel approach to multi attribute group decision making based on trapezoidal interval type-2 fuzzy soft sets”. Applied Mathematical Modelling, 37(7), 4948-4971, 2013.
  • Kahraman C, Kaya İ, Cebi S. “A comparative analysis for multiattribute selection among renewable energy alternatives using fuzzy axiomatic design and fuzzy analytic hierarchy process”. Energy, 34(10), 1603-1616, 2009.
  • Chen SM, Lee LW. “Fuzzy multiple attributes group decision-making based on the ranking values and the arithmetic operations of interval type-2 fuzzy sets”. Expert Systems with Applications, 37(1), 824-833, 2010.
  • Chen SM, Yang M W, Lee L W, Yang S W. “Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets”. Expert Systems with Applications, 39(5), 5295-5308, 2012.
  • Lou CW, Dong MC. “Modeling data uncertainty on electric load forecasting based on type-2 fuzzy logic set theory”. Engineering Applications of Artificial Intelligence, 25(8), 1567-1576, 2012.
  • Paternain D, Jurio A, Barrenechea E, Bustince H, Bedregal B, Szmidt E. “An alternative to fuzzy methods in decision-making problems”. Expert Systems with Applications, 39(9), 7729-7735, 2012.
  • Wang W, Liu X, Qin Y. “Multi-attribute group decision making models under interval type-2 fuzzy environment”. Knowledge-Based Syst., 30, 121-128, 2012.
  • Celik E, Bilisik O N, Erdogan M, Gumus A T, Baracli H. “An integrated novel interval type-2 fuzzy MCDM method to improve customer satisfaction in public transportation for Istanbul”. Transportation Research Part E: Logistics and Transportation Review, 58, 28-51, 2013.
  • Chen TY. “A linear assignment method for multiple-criteria decision analysis with interval type-2 fuzzy sets”. Applied Soft Computing, 13(5), 2735-2748, 2013.
  • Chen TY,Chang CH, Rachel LJ. “The extended QUALIFLEX method for multiple criteria decision analysis based on interval type-2 fuzzy sets and applications to medical decision making”. European Journal of Operational Research, 226(3), 615-625, 2013.
  • Hu J, Zhang Y, Chen X, Liu Y. “Multi-criteria decision making method based on possibility degree of interval type-2 fuzzy number”. Knowledge-Based Systems, 43, 21–29, 2013.
  • Chen TY. “An ELECTRE-based outranking method for multiple criteria group decision making using interval type-2 fuzzy sets”. Information Sciences, 263, 1-21, 2014.
  • Kiliç M, Kaya İ. “Investment project evaluation by a decision making methodology based on type-2 fuzzy sets”. Applied Soft Computing, 27, 399-410, 2015.
  • Daǧdeviren M, Yavuz S, Kilinç N. “Weapon selection using the AHP and TOPSIS methods under fuzzy environment”. Expert Systems with Applications, 36(4), 8143-8151, 2009.
  • Chen CT, Lin CT, Huang SF. “A fuzzy approach for supplier evaluation and selection in supply chain management”. International Journal of Production Economics, 102(2), 289-301, 2006.
  • Saima H, Jaafar J, Belhaouari S, Jillani T. “ARIMA based interval type-2 fuzzy model for forecasting”. International Journal of Computer Applications, 28(3), 17-21, 2011.
  • Torshizi AD, Zarandi MHF, Zakeri H. “On type-reduction of type-2 fuzzy sets: A review”. Applied Soft Computing, 27, 614-627, 2015.
  • Chen SM, Yang MW, Lee LW, Yang SW. “Fuzzy multiple attributes group decision-making based on ranking interval type-2 fuzzy sets”. Expert Systems with Applications, 39(4), 5295-5308, 2012.
  • Celik E, Gumus AT, Alagoz M. “A trapezoidal type-2 fuzzy MCDM method to identify and evaluate critical success factors for humanitarian relief logistics management”. Journal of Intelligent & Fuzzy Systems, 27(6), 2847-2855, 2014.
  • Dereli T, Baykasoglu A, Altun K, Durmusoglu A, Türksen I. B. “Industrial applications of type-2 fuzzy sets and systems: A concise review”. Computers in Industry, 62(2), 125-137, 2011.
  • Abdullah L, Najib L. “A new type-2 fuzzy set of linguistic variables for the fuzzy analytic hierarchy process”. Expert Syst. Appl., 41(7), 3297–3305, 2014.
  • Türkşen IB. “Type 2 representation and reasoning for CWW”. Fuzzy Sets and Systems, 127(1), 17-36, 2002.
  • Liao H, Xu Z. “A VIKOR-based method for hesitant fuzzy multi-criteria decision making”. Fuzzy Optimization and Decision Making, 12(4), 373-392, 2013.
  • Mendel J M, John R, Liu F. “Interval type-2 fuzzy logic systems made simple”. Fuzzy Systems, IEEE Transactions, 14(6), 808-821, 2006.
  • John R, Coupland S. “Type-2 fuzzy logic and the modelling of uncertainty in applications”. Human-Centric Information Processing Through Granular Modelling, 182, 185-201, 2009.
  • Zadeh LA. “The concept of a linguistic variable and its application to approximate reasoning-1”. Information Sciences, 8(4), 199-249,1975.
  • Li D F, Yang J. “A difference-index based ranking method of trapezoidal intuitionistic fuzzy numbers and application to multiattribute decision making”. Mathematical and Computational Applications, 20(1), 25-38, 2015.
  • Wen X, Ouyang J, Liu Y. “A method of hybrid multiple attributes group decision making with risk considering decision-makers' confidence”. Mathematical and Computational Applications, 20(1), 62-75, 2015.
  • Ballı S., Karasulu B. “Bulanık karar verme sistemlerinde paralel hesaplama”. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 19(2), 61-67, 2013.
  • Zouggari A, Benyoucef L. “Simulation based fuzzy TOPSIS approach for group multi-criteria supplier selection problem”. Engineering Applications of Artificial Intelligence, 25(3), 507-519, 2012.
  • Dickson GW. “An analysis of vendor selection systems and decisions”. Journal of Purchasing, 2, 5-17, 1966.
  • Araz C, Ozkarahan I. “Supplier evaluation and management system for strategic sourcing based on a new multicriteria sorting procedure”. International Journal of Production Economics, 106(2), 585-606, 2007.
  • Amid A, Ghodsypour SH, O’Brien C. 2006. “Fuzzy multiobjective linear model for supplier selection in a supply chain”. International Journal of Production Economics, 104(2), 394-407.
  • Ha SH, Krishnan R. “A hybrid approach to supplier selection for the maintenance of a competitive supply chain”. Expert Systems with Applications, 34(2), 1303-1311, 2008.
  • Weber CA, Current, JR, Benton WC. “Vendor selection criteria and methods”. European Journal of Operational Research, 50(1), 2-18, 1991.
  • Kumar M, Vrat, P, Shankar R. “A fuzzy programming approach for vendor selection problem in a supply chain”. International Journal of Production Economics, 101(2), 273-285, 2006.
  • Bevilacqua M, Ciarapica FE, Giacchetta G. “A fuzzy-QFD approach to supplier selection”. Journal of Purchasing & Supply Management, 12(1), 14-27, 2006.
  • Liu FH, Hai HL. “The voting analytic hierarchy process method for selecting supplier”. International Journal of Production Economics, 97(3), 308-317, 2005.
  • Chen CT, Lin CT, Huang S. “A fuzzy approach for supplier evaluation and selection in supply chain management”. International Journal of Production Economics, 102(2), 289-301, 2006.
  • Omurca S I. “An intelligent supplier evaluation, selection and development system”. Applied Soft Computing, 13(1), 690-697, 2013.
  • Dogan I, Aydin N. “Combining bayesian networks and total cost of ownership method for supplier selection analysis”. Computers & Industrial Engineering, 61(4), 1072-1085, 2011.
  • Yue Z, Jia Y. ”A group decision making model with hybrid intuitionistic fuzzy information”. Computers & Industrial Engineering, 87, 202-212, 2015.
  • Ayağ Z, Samanlioglu F. “An intelligent approach to supplier evaluation in automotive sector”. Journal of Intelligent Manufacturing, 27(5), 1-15, 2014.
  • Beikkhakhian Y, Javanmardi M, Karbasian M, Khayambashi B. “The application of ISM model in evaluating agile suppliers selection criteria and ranking suppliers using fuzzy TOPSIS-AHP methods”. Expert Systems with Applications, 42(15-16), 6224-6236, 2015.
  • Wood DA. “Supplier selection for development of petroleum industry facilities, applying multi-criteria decision making techniques including fuzzy and intuitionistic fuzzy TOPSIS with flexible entropy weighting”. Journal of Natural Gas Science and Engineering, 28, 594-612, 2016.
  • Montazer GA, Saremi HQ, Ramezani M. “Design a new mixed expert decision aiding system using fuzzy ELECTRE III method for vendor selection”. Expert Systems with Applications, 36(8), 10837-10847, 2009.
  • Awasthi A, Kannan G. “Green supplier development program selection using NGT and VIKOR under fuzzy environment”. Computers & Industrial Engineering, 91, 100-108, 2016.
Konular Mühendislik ve Temel Bilimler
Dergi Bölümü Makale
Yazarlar

Yazar: Berk Ayvaz

Yazar: Ali Osman Kuşakcı

Bibtex @ { pajes298010, journal = {Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi}, issn = {1300-7009}, eissn = {2147-5881}, address = {Pamukkale Üniversitesi}, year = {}, volume = {23}, pages = {70 - 80}, doi = {}, title = {Tedarikçi seçimi için TOPSIS tabanlı ikizkenar yamuk tip-2 bulanık çok kriterli karar verme metodu: Tekstil sektöründe bir uygulama}, key = {cite}, author = {Ayvaz, Berk and Kuşakcı, Ali Osman} }
APA Ayvaz, B , Kuşakcı, A . (). Tedarikçi seçimi için TOPSIS tabanlı ikizkenar yamuk tip-2 bulanık çok kriterli karar verme metodu: Tekstil sektöründe bir uygulama. Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi, 23 (1), 70-80. Retrieved from http://www.dergipark.gov.tr/pajes/issue/28108/298010
MLA Ayvaz, B , Kuşakcı, A . "Tedarikçi seçimi için TOPSIS tabanlı ikizkenar yamuk tip-2 bulanık çok kriterli karar verme metodu: Tekstil sektöründe bir uygulama". Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 23 (): 70-80 <http://www.dergipark.gov.tr/pajes/issue/28108/298010>
Chicago Ayvaz, B , Kuşakcı, A . "Tedarikçi seçimi için TOPSIS tabanlı ikizkenar yamuk tip-2 bulanık çok kriterli karar verme metodu: Tekstil sektöründe bir uygulama". Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi 23 (): 70-80
RIS TY - JOUR T1 - Tedarikçi seçimi için TOPSIS tabanlı ikizkenar yamuk tip-2 bulanık çok kriterli karar verme metodu: Tekstil sektöründe bir uygulama AU - Berk Ayvaz , Ali Osman Kuşakcı Y1 - 2018 PY - 2018 N1 - DO - T2 - Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi JF - Journal JO - JOR SP - 70 EP - 80 VL - 23 IS - 1 SN - 1300-7009-2147-5881 M3 - UR - Y2 - 2018 ER -
EndNote %0 Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi Tedarikçi seçimi için TOPSIS tabanlı ikizkenar yamuk tip-2 bulanık çok kriterli karar verme metodu: Tekstil sektöründe bir uygulama %A Berk Ayvaz , Ali Osman Kuşakcı %T Tedarikçi seçimi için TOPSIS tabanlı ikizkenar yamuk tip-2 bulanık çok kriterli karar verme metodu: Tekstil sektöründe bir uygulama %D 2018 %J Pamukkale Üniversitesi Mühendislik Bilimleri Dergisi %P 1300-7009-2147-5881 %V 23 %N 1 %R %U