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Journals / Mühendislik Bilimleri ve Tasarım Dergisi / 2026 / Cilt: 9 Sayı: 3

DENTAL SUPPLIER SELECTION WITH TOPSIS METHOD BY USING LP METHODOLOGY

TOPSİS YÖNTEMİ İLE ORTODONTİK TEDARİKÇİ SEÇİMİ

Babek Erdebilli(ANKARA YILDIRIM BEYAZIT UNIVERSITY)0000-0001-8860-3903
İlknur Güneşli(ANKARA YILDIRIM BEYAZIT ÜNİVERSİTESİ)0000-0003-3069-2565
Seda Şahin(ANKARA YILDIRIM BEYAZIT ÜNİVERSİTESİ)0000-0003-0924-643X
Pages
940–951
Publication Date
2021-09-21
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

At the end of the study, it is foreseen that with the right selection of suppliers, The competitive power of companies in the market and end user satisfaction will increase.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Dental supplier selection is a process that allows companies to choose their suppliers correctly in the light of evaluations.
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Key Findings & Data:TOPSIS method integrated intuitionistic fuzzy set is used in this study.
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Conclusion & Impact:At the end of the study, it is foreseen that with the right selection of suppliers, The competitive power of companies in the market and end user satisfaction will increase.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Sezgisel Bulanık Küme · Doğrusal Programlama (LP) Metodolojisi · Tedarikçi Seçimi

Abstract

Dental supplier selection is a process that allows companies to choose their suppliers correctly in the light of evaluations. Choosing the right dental suppliers is an important factor both for the efficiency of dental treatment and handling an impressive supply chain. Dental supplier selection is a multi-criterion group decision-making (MCDM) problem that contains many different criterion about the decision-makers generally ambiguous information. TOPSIS method integrated intuitionistic fuzzy set is used in this study. Real-life problems include many unpredictability and defects. Experts are involved in assigning the weights of the criterion in this study. Linear programming (LP) methodology has applied for the ranking of these weights of criterion. Then, the LP methodology is carried out and it was ensured that the appropriate orthodontic bracket suppliers were selected. This is a specific multi-criterion decision making problem. The study was followed together with the sensitivity analyses of the results. At the end of the study, it is foreseen that with the right selection of suppliers, The competitive power of companies in the market and end user satisfaction will increase.

Özet

Ortodontik Tedarikçi seçimi, firmaların ve şirketlerin tedarikçilerini değerlendirmeler ışığında daha doğru ve daha isabetli seçmelerini sağlayan bir süreçtir. Günümüzde Uygun Ortodontik sarf malzemesi tedarikçilerini seçmek, hem diş tedavisinin verimliliği hem de etkileyici bir tedarik zincirinin ele alınması için önemli bir faktördür. Ortodontik Tedarikçi seçimi, karar vericiler için genellikle birçok farklı kriter içeren çok kriterli grup karar verme (ÇKKV) problem olarak ele alınmaktadır. Bu çalışmada ÇKKV yöntemlerinde olan TOPSIS yöntemi ile bütünleştirilmiş sezgisel bulanık küme (BSBK) kullanılmıştır. Gerçek hayat problemleri birçok öngörülemezliği, karmaşıklığı ve kusuru içermektedir. Gerçekleştirilen çalışmada kriterin ağırlıklarının belirlenmesinde uzman görüşlerine yer verilmiştir. Daha sonra bu kriter ağırlıklarının sıralanması için ayrıca doğrusal programlama (DP) metodolojisi uygulanmış ve bu kapsamda uygun ortodontik braket tedarikçilerinin seçilmesi sağlanmıştır. Ele alınan konu, belirli birçok kriterli karar verme problemidir. Çalışma, sonuçları duyarlılık analizleri ile incelenmiştir. Makalenin sonunda, doğru Ortodontik Tedarikçi seçimi ile piyasada var olan şirket ve firmaların pazardaki rekabet gücünün ve son kullanıcı memnuniyetinin artacağı öngörülmektedir.

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Cite This Article

Erdebilli, B., Güneşli, İ., Şahin, S. (2021). DENTAL SUPPLIER SELECTION WITH TOPSIS METHOD BY USING LP METHODOLOGY. Mühendislik Bilimleri ve Tasarım Dergisi, Cilt: 9 Sayı: 3, 940–951. https://doi.org/10.21923/jesd.818868

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References (30)

  1. Atanassov K. T. (1994). Operators over interval valued intuitionistic fuzzy sets. Fuzzy Sets and Systems, 64(2), 159–174. https://doi.org/10.1016/0165-0114(94)90331-X
  2. Biderci H., Canbaz B., Ergonomic Room Selection with Intuitive Fuzzy TOPSIS Method, Procedia Computer Science, Volume 158, 2019, Pages 58-67, ISSN 1877-0509, https://doi.org/10.1016/j.procs.2019.09.153
  3. Boran, F. E., Genç S., Kurt M., & Akay D. (2009). A multi-criterion intuitionistic fuzzy group decision making for supplier selection with TOPSIS method. Expert Systems with Applications, 36(8), 11363–11368. https://doi.org/10.1016/j.eswa.2009.03.039
  4. Chen C.T., Lin C.T., Huang S.F., (2006). A fuzzy approach for supplier evaluation and selection in supply chain management. Doi: 10.1016/j.ijpe.2005.03.009
  5. Chou S. Y., Chang Y. H. (2008). A decision support system for supplier selection based on a strategy-aligned fuzzy SMART approach. Expert Systems with Applications, 34(4), 2241–2253. https://doi.org/10.1016/j.eswa.2007.03.001
  6. Chou S.Y., Chang Y.H. (2008). A decision support system for supplier selection based on a strategy-aligned fuzzy SMART approach, Expert Systems with Applications Volume 34, Issue 4, Pages 2241-2253. https://doi.org/10.1016/j.eswa.2007.03.001
  7. Dargi A., Anjomshoae, A., Galankashi M. R., Memari A., Tap M.B.M (2014). Supplier Selection: A Fuzzy-ANP Approach, Volume 31, 2014, Pages 691-700, Procedia Computer Science. https://doi.org/10.1016/j.procs.2014.05.317
  8. Dickson, G. W. (1966). An Analysis of Vendor Selection Systems and Decisions. Journal of Purchasing, 2(1), 5–17. https://doi.org/10.1111/j.1745-493X.1966.tb00818.x
  9. Erginel N. (2016). Fuzzy multi-objective decision model for calibration supplier selection problem, Computers & Industrial Engineering. DOI: 10.1016/j.cie.2016.10.017
  10. Galankashi M., Helmi S. A., Hashemzahi P. (2016). Supplier selection in automobile industry: A mixed balanced scorecard–fuzzy AHP approach, Alexandria Engineering Journal Volume 55, Issue 1, March 2016, Pages 93-100. https://doi.org/10.1016/j.aej.2016.01.005
  11. Gregory R.E., Journal of Purchasing and Materials Management, Source Selection: A Matrix Approach, 1986, https://doi.org/10.1111/j.1745-493X.1986.tb00159.x
  12. Gulsun Nakiboglu & Berna Bulgurcu (2021) Supplier selection in a Turkish textile company by using intuitionistic fuzzy decision-making, The Journal of The Textile Institute, 112:2, 322-332, DOI: 10.1080/00405000.2020.1747675
  13. Haq, A. N., & Kannan, G. (2006). Fuzzy analytical hierarchy process for evaluating and selecting a vendor in a supply chain model. International Journal of Advanced Manufacturing Technology, 29(7–8), 826–835. https://doi.org/10.1007/s00170-005-2562-8
  14. Jain N., (2019). Sustainable supplier selection under must-be criteria through Fuzzy inference system, Journal of Cleaner Production. DOI: 10.1016/j.jclepro.2019.119275
  15. Kara S.S. (2011). Supplier selection with an integrated methodology in unknown environment, Expert Systems with Applications Volume 38, Issue 3, Pages 2133-2139. https://doi.org/10.1016/j.eswa.2010.07.154
  16. Kaya R., Yet B. (2019). Building Bayesian networks based on DEMATEL for multiple criterion decision problems. Procedia Computer Science Volume 133, 2018, Pages 905-912. DOI: 10.1016/j.eswa.2019.05.053
  17. Kumar S., Kumar S., Barman A. (2018). Supplier selection using fuzzy TOPSIS multi criteria model for a small scale steel manufacturing unit. Procedia Computer Science Volume 133, 2018, Pages 905-912. https://doi.org/10.1016/j.procs.2018.07.097
  18. Lei W. Gao Q. (2013). Linguistic terms description of separate index level. International Journal of Environmental Protection and Policy Vol. 1, No. 4, 2013, pp. 68-75. https://doi.org/10.11648/j.ijepp.20130104.14
  19. Nydick, R. L., Hill, R.P.,(1992), Using the Analytic Hierarchy Process to Structure the Supplier Selection Procedure, International Journal of Purchasing and Materials Management, https://doi.org/10.1111/j.1745-493X.1992.tb00561.x
  20. Önüt S., Kara S. S., & Işik E. (2009). Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company. Expert Systems with Applications, 36(2 PART 2), 3887–3895. https://doi.org/10.1016/j.eswa.2008.02.045
  21. Rouyendegh B.D. (2014). Supplier Selection Using Integrated Fuzzy TOPSIS and MCGP, Procedia-Social and Behavioral Sciences 116, 3957-3970. https://doi.org/10.1016/j.sbspro.2014.01.874
  22. Sarkis, J., & Talluri, S. (2002). A Model for Strategic Supplier Selection. Journal of Supply Chain Management, 38(4), 18–28. https://doi.org/10.1111/j.1745-493X.2002.tb00117.x
  23. Sindhu, M. S., Rashid, T., Kashif, A., & Guirao, J. L. G. (2019). Multiple Criterion Decision Making Based on Probabilistic Interval-Valued Hesitant Fuzzy Sets by Using LP Methodology. Discrete Dynamics in Nature and Society, 2019. https://doi.org/10.1155/2019/1527612
  24. Soukup W.R., (1987), “Supplier selection strategies”, Journal of Purchasing and Materials Management, 23, 77 – 82.
  25. Timmerman, E., 1986. An approach to vendor performance evaluation. Journal of Purchasing and Materials Management 22, 2–8.
  26. Thompson, K. N., (1990), Vendor Profile Analysis, Journal of Purchasing and Materials Management, https://doi.org/10.1111/j.1745-493X.1990.tb00494.x
  27. Weber, C. A., Current, J. R., & Benton, W. C. (1991). Vendor selection criterion and methods. European Journal of Operational Research, 50(1), 2–18. https://doi.org/10.1016/0377-2217(91)90033-R
  28. Xian S. and Guo, H., Novel supplier grading approach based on interval probability hesitant fuzzy linguistic TOPSIS, 2020 https://doi.org/10.1016/j.engappai.2019.103299.
  29. You X.Y., You J.X., Liu H.C., Zhen L. (2015). Group multi-criteria supplier selection using an extended VIKOR method with interval 2-tuple linguistic information. https://doi.org/10.1016/j.eswa.2014.10.004
  30. Zadeh L.A. (1965). Fuzzy Sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X