Küresel Bulanık EDAS ve Bir Uygulama

Öz

İnsan tercihlerindeki belirsizliği ve kesinsizliği temsil etmek amacıyla 1960'larda bulanık kümeler kavramı ortaya atılmış ve daha sonraki süreçte bir çok farklı bulanık küme tanımı geliştirilmiştir. Bu gelişmelerden oldukça yeni bir tanesi olan küresel bulanık kümeler (KBK), karar vericilere kapsamlı bir tercih alanı vererek bu amacı desteklemektedir. KBK'in ayırt edici özelliği, üyelik, üye-olmama ve tereddüt derecelerinin kareler toplamının [0,1] aralığında olması ve her bir unsurun aynı aralık içinde bağımsız olarak tanımlanabilmesidir. Bu çalışma ile, oldukça yeni ancak yazında sıkça kendine yer bulan bir çok ölçütlü karar verme yöntemi olan EDAS (Evaluation Based on Distance from Average Solution – Ortalama Çözüme Olan Uzaklığa Dayalı Değerlendirme), küresel bulanık ortam için uyarlanmaktadır. Entropi tabanlı nesnel ölçüt ağırlıklandırma, daha uzun veri toplama süresi gibi öznel ağırlıklandırma yöntemlerinin dezavantaj yaratan potansiyel etkilerinden kaçınmak için EDAS'ın bu yeni sürümüyle entegre edilmiştir. Önerilen yeni versiyon, eklemeli imalat (additive manufacturing) için bir ürün tasarımı seçme problemi örneğinde uygulanmıştır.

Anahtar Kelimeler

• EDAS
• küresel bulanık kümeler
• entropi ölçüsü
• dilsel değerlendirme

Spherical Fuzzy Version of EDAS and An Application

Öz

Several fuzzy set concepts have been developed after the first invention of fuzzy sets in 1960s with the aim of demonstrating the uncertainty and vagueness in human preferences. Spherical fuzzy sets (SFS) as a recent one of these developments support this aim by giving a comprehensive preference domain to decision makers. The distinctive feature of SFS is its rule saying that the squared sum of membership, non-membership, and hesitancy degrees should be within the interval of [0,1] while its each element is independently assigned within the same interval. With this study, EDAS (Evaluation Based on Distance from Average Solution), one of the younger but stronger multiple attribute decision making tools is modified for spherical fuzzy environment. Entropy-based objective attribute weighting is also integrated with this novel version of EDAS to avoid the undesired potential effects of subjective weighting such as longer data collection time. The novel version proposed is applied in an example of a product design selection problem for additive manufacturing.

Anahtar Kelimeler

• EDAS
• spherical fuzzy sets
• entropy measure
• linguistic assessment

Kaynakça

1. [1] Aldalou, E., Perçin, S. (2020). Financial Performance Evaluation of Food and Drink Index Using Fuzzy MCDM Approach. Int. J. Econ. Innov., 6(1), 1-19.
2. [2] Atanassov, K.T. (1986). INTUITIONISTIC FUZZY SETS. Fuzzy Set. Syst., 20, 87-96.
3. [3] Aydoğdu, A., Gül, S. (2020). A novel entropy proposition for spherical fuzzy sets and its application in multiple attribute decision-making. Int. J. Intell. Syst., 35(9), 1354-1374.
4. [4] Darko, A.P., Liang, D. (2020). Some q-rung orthopair fuzzy Hamacher aggregation operators and their application to multiple attribute group decision making with modified EDAS method. Eng. Appl. Artif. Intel., 87, 103259.
5. [5] Erkayman, B., Khorshidi, M., Usanmaz, B. (2018). AN INTEGRATED FUZZY APPROACH FOR ERP DEPLOYMENT STRATEGY SELECTION UNDER CONFLICTING CRITERIA. Atatürk Üniv. İİB Dergisi, 32(3), 807-823.
6. [6] Han, L., Wei, C. (2020). An Extended EDAS Method for Multicriteria Decision-Making Based on Multivalued Neutrosophic Sets. Complexity, 7578507, 9 pages.
7. [7] Kahraman, C., Keshavarz Ghorabaee, M., Zavadskas, E.K., Cevik Onar, S., Yazdani, M., Oztaysi, B. (2017). INTUITIONISTIC FUZZY EDAS METHOD: AN APPLICATION TO SOLID WASTE DISPOSAL SITE SELECTION. J. Environ. Eng. Landsc., 25(01), 1-12.
8. [8] Karaşan, A., Kahraman, C. (2018a). A novel interval-valued neutrosophic EDAS method: prioritization of the United Nations national sustainable development goals. Soft Comput., 22, 4891-4906.

9. [9] Karaşan, A., Kahraman, C. (2018b). Interval-Valued Neutrosophic Extension of EDAS Method. In: Kacprzyk J, Szmidt E, Zadrozny S, Atanassov KT, Krawczak M (eds) Advances in Fuzzy Logic and Technology 2017, Proceedings of EUSFLAT’17, September 11-15, Warsaw, Poland & IWIFSGN’17, September 13-15, Warsaw, Poland. Advances in Intelligent Systems and Computing, Switzerland: Springer 642, 343-357.
10. [10] Kas Bayrakdaroğlu, F., Kundakcı, N. (2019). BULANIK EDAS YÖNTEMİ İLE AR-GE PROJESİ SEÇİMİ. Uluslararası İkt. ve İd. İnc. Dergisi, 24, 151-170.
11. [11] Keshavarz Ghorabaee, M., Zavadskas, E.K., Olfat, L., Turskis, Z. (2015). Multi-Criteria Inventory Classification Using a New Method of Evaluation Based on Distance from Average Solution (EDAS). Informatica, 26(3), 435-451.
12. [12] Koksalmis, E., Kabak, Ö. (2019). Deriving decision makers’ weights in group decision making: An overview of objective methods. Inform. Fusion, 49, 146-160.
13. [13] Kutlu Gündoğdu, F. (2020). Principals of Spherical Fuzzy Sets. In: Kahraman C, Cebi S, Cevik Onar S, Oztaysi B, Tolga A, Sari I (eds) Intelligent and Fuzzy Techniques in Big Data Analytics and Decision Making (INFUS’19), July 23-25, İstanbul, Turkey. Advances in Intelligent Systems and Computing, Switzerland: Springer 1029, 15-23.
14. [14] Kutlu Gündoğdu, F., Kahraman, C. (2019a). Spherical fuzzy sets and spherical fuzzy TOPSIS method. J. Intell. Fuzzy Syst., 36(1), 337-352.
15. [15] Kutlu Gündoğdu, F., Kahraman, C. (2019b). A novel fuzzy TOPSIS method using emerging interval-valued spherical fuzzy sets. Eng. Appl. Artif. Intel., 85, 307-323.
16. [16] Kutlu Gündoğdu, F., Kahraman, C. (2020a). A novel spherical fuzzy analytic hierarchy process and its renewable energy application. Soft Comput., 24, 4607-4621.
17. [17] Kutlu Gündoğdu, F., Kahraman, C. (2020b). A novel spherical fuzzy QFD method and its application to the linear delta robot technology development. Eng. Appl. Artif. Intel., 87, 103348.
18. [18] Li, Y.Y., Wang, J.Q., Wang, T.L. (2019). A Linguistic Neutrosophic Multi-criteria Group Decision-Making Approach with EDAS Method. Arab. J. Sci. Eng., 44, 2737-2749.
19. [19] Li, Z., Wei, G., Wang, R., Wu, J., Wei, C., Wei, Y. (2020). EDAS METHOD FOR MULTIPLE ATTRIBUTE GROUP DECISION MAKING UNDER Q-RUNG ORTHOPAIR FUZZY ENVIRONMENT. Technol. Econ. Dev. Eco., 26(1), 86-102.
20. [20] Liang, Y. (2020). An EDAS Method for Multiple Attribute Group Decision-Making under Intuitionistic Fuzzy Environment and Its Application for Evaluating Green Building Energy-Saving Design Projects. Symmetry, 12, 484.
21. [21] Mishra, A.R.., Mardani, A., Rani, P., Zavadskas, E.K. (2020). A novel EDAS approach on intuitionistic fuzzy set for assessment of health-care waste disposal technology using new parametric divergence measures. J. Clean. Prod., 272, 122807.
22. [22] Mohagheghi, V., Mousavi, S.M. (2019). D-WASPAS: Addressing Social Cognition in Uncertain Decision-Making with an Application to a Sustainable Project Portfolio Problem. Cogn. Comput., 12, 619-641.
23. [23] Mukul, E., Büyüközkan, G., Güler, M. (2019). STRATEGIC ANALYSIS OF INTELLIGENT TRANSPORTATION SYSTEMS. Beykoz Akad. Dergisi, Özel Sayı, 148-158.
24. [24] Özbek, A. (2019). TÜRKİYE’DEKİ İLLERİN EDAS VE WASPAS YÖNTEMLERİ İLE TAŞANABİLİRLİK KRİTERLERİNE GÖRE SIRALANMASI. Kırıkkale Üniv. SB Dergisi, 9(1), 177-200.
25. [25] Özmen, M. (2020). OECD ÜLKELERİNİN TELEKOMÜNİKASYON SEKTÖRÜ AÇISINDAN SMAA-EDAS YÖNTEMİ İLE DEĞERLENDİRİLMESİ. NOHU J. Eng. Sci., 9(1), 224-237.
26. [26] Peng, X., Liu, C. (2017). Algorithms for neutrosophic soft decision making based on EDAS, new similarity measure and level soft set. J. Intell. Fuzzy Syst., 32, 955-968.
27. [27] Schitea, D., Deveci, M., Iordache, M., Bilgili, K., Akyurt, İ.Z., Iordache, I. (2019). Hydrogen mobility roll-up site selection using intuitionistic fuzzy sets based WASPAS, COPRAS and EDAS. Int. J. Hydrogen Energ., 44, 8585-8600.
28. [28] Smarandache, F. (1999). A unifying field in logics neutrosophy: neutrosophic probability, set and logic, Rehoboth: American Research Press.
29. [29] Supciller, A.A., Toprak, F. (2020). Selection of wind turbines with multi-criteria decision making techniques involving neutrosophic numbers: A case from Turkey. Energy, 207, 118237.
30. [30] Ulutaş, A. (2018). ENTROPİ TABANLI EDAS YÖNTEMİ İLE LOJİSTİK FİRMALARININ PERFORMANS ANALİZİ. Uluslararası İkt. ve İd. İnc. Dergisi, 23, 53-66.
31. [31] Wang, H., Smarandache, F., Zhang, Y.Q., Sunderraman, R. (2005). Interval Neutrosophic Sets and Logic: Theory and Applications in Computing, Hexis, USA.
32. [32] Wang, H., Smarandache, F., Zhang, Y.Q., Sunderraman, R. (2010). Single valued neutrosophic sets. In: Smarandache F (ed) Multispace & Multistructure. Neutrosophic Transdisciplinarity Vol. IV. North-European Scientific Publishers, Hanko, Finland, 410-413.
33. [33] Wang, P., Wang, J., Wei, G. (2019). EDAS method for multiple criteria group decision making under 2-tuple linguistic neutrosophic environment. J. Intell. Fuzzy Syst., 37(2), 1597-1608.
34. [34] Xu, D., Cui, X., Xian, H. (2020). An Extended EDAS Method with a Single-Valued Complex Neutrosophic Set and Its Application in Green Supplier Selection. Mathematics, 8, 282.
35. [35] Yager, R.R. (2013). Pythagorean fuzzy subsets. Proceedings of Joint IFSA World Congress and NAFIPS Annual Meeting, June 24-28, 2013, Edmonton, Canada, 57-61.
36. [36] Yager, R.R. (2017). Generalized Orthopair Fuzzy Sets. IEEE Trans. Fuzzy Syst., 25(5), 1222-1230.
37. [37] Zadeh, L.A. (1965). Fuzzy sets. Inform. Control, 8, 338-353.