Araştırma Makalesi
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Bebek Arabası Seçimi İçin Tereddütlü Bulanık Dilsel Karar Yaklaşımı

Yıl 2021, Cilt: 10 Sayı: 4, 1464 - 1473, 31.12.2021
https://doi.org/10.17798/bitlisfen.960814

Öz

Bebek sahibi olmak ebeveynlerin yaşamına yeni değişimler ve zorlukları da beraberinde getirir. Bebeğe rahat bir yaşam sunabilmek için gereken pek çok şey vardır. Çoğu insanın sınırlı ekonomik kaynakları olmasından ötürü, satın alınacak nesnelerin belirlenmesi ebeveynler için önemli bir karar haline gelmektedir. Ayrıca, alınması gereken her bir nesne (yatak, kıyafet, besleme ekipmanları, bebek arabası, vb.) için çok sayıda seçenek vardır. Bu nedenle, seçenekler arasında bir seçim yapmak gereklidir. Farklı seçeneklerin diğerleri üzerinde farklı yönlerden üstünlükleri söz konusudur. Farklı yönleri dikkate almak iyi bir karar vermeyi sağlayacaktır, ebeveynlerin de bu yönde hareket etmelidir. Bu çalışmada, ebeveynlerin bebek arabası seçimi kararı için analitik bir karar modeli geliştirmek amaçlanmıştır. Tereddütlü bulanık dilsel terimler kümesi (Hesitant Fuzzy Linguistic Terms Set = HFLTS) yaklaşımı, karar vericilerin dilsel bir değişkenin çeşitli değerleri arasında kararsız kaldığı kesin olmayan durumları modellemek için geliştirilmiştir. Bu yaklaşım kullanılarak dilsel bilginin çıkarımı iyileştirilmekte ve karar vericilerin düşünceleri karar modellerinde daha iyi temsil edilebilmektedir. Ebeveynlerin kararsız hislere sahip olacağı düşüncesi altında HFLTS temelli grup karar verme yaklaşımı en iyi bebek arabasını bulmak için kullanılmıştır. Yaklaşımın uygulanabilirliğini göstermek üzere bir uygulama çalışması sunulmuş ve önerilen modelin bebek arabası seçiminde kullanışlı olduğu görülmüştür.

Kaynakça

  • Zadeh, L. A. 1965. Fuzzy sets. Information and Control, 8: 338-&.
  • Bellman R. E., Zadeh, L. A. 1970. Decision-making in a fuzzy environment. Management Science Series B-Application, 17: B141-B164.
  • Zadeh, L. A. 1975. Concept of a linguistic variable and ıts application to approximate reasoning-1. Information Sciences, 8: 199-249.
  • Atanassov, K. T. 1986. Intuitionistic fuzzy-sets. Fuzzy Sets and Systems, 20: 87-96.
  • Smaradache, F. 2002. A unifying field in logics: neutrosophic logic. Multiple-Valued Logic, 8: 385–438.
  • Torra, V. 2010. Hesitant fuzzy sets. International Journal of Intelligent Systems, 25: 529-539.
  • Rodriguez, R. M., Martinez, L. Herrera, F. 2012. Hesitant fuzzy linguistic term sets for decision making. IEEE Transactions on Fuzzy Systems, 20: 109-119.
  • Yavuz, M., Oztaysi, B., Onar, S. C., Kahraman, C. 2015. Multi-criteria evaluation of alternative fuel vehicles via a hierarchical hesitant fuzzy linguistic model. Expert Systems with Applications, 42: 2835–2848.
  • Wang, J., Wang J. Q., Zhang, H. Y. 2016. A likelihood-based TODIM approach based on multi hesitant fuzzy linguistic information for evaluation in logistics outsourcing. Computers & Industrial Engineering, 99: 287-299.
  • Sun, R. X., Hu, J. H., Zhou J. D., Chen, X. H. 2018. A hesitant fuzzy linguistic projection based mabac method for patients' prioritization. International Journal of Fuzzy Systems, 20: 2144-2160.
  • Wu, Z. B., Xu, J. P., Jiang X. L., Zhong, L. 2019. Two MAGDM models based on hesitant fuzzy linguistic term sets with possibility distributions: VIKOR and TOPSIS. Information Sciences, 473: 101-120.
  • Ji, P., Zhang H. Y., Wang, J. Q. 2018. A projection-based outranking method with multi hesitant fuzzy linguistic term sets for hotel location selection. Cognitive Computation, 10: 737-751.
  • Liao, H. C., Wu, X. L., Liang, X. D., Xu, J. P., Herrera, F. 2018. A new hesitant fuzzy linguistic ORESTE method for hybrid multicriteria decision making. IEEE Transactions on Fuzzy Systems, 26: 3793-3807, 2018.
  • Xue, Y. X., You, J. X., Zhao X. F., Liu, H. C. 2016. An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information. International Journal of Production Research, 54: 5452-5467.
  • Wu, Y. N., Wang, Y., Chen, K. F., Xu C. B., Li, L. W. Y. 2017. Social sustainability assessment of small hydropower with hesitant PROMETHEE method. Sustainable Cities and Society, 35: 522-537.
  • Wu Y. N., Zhou, J. L. 2019. Risk assessment of urban rooftop distributed PV in energy performance contracting (EPC) projects: An extended HFLTS-DEMATEL fuzzy synthetic evaluation analysis. Sustainable Cities and Society, 47: 101524.
  • Liao, H. C., Mi, X. M., Yu Q., Luo, L. 2019. Hospital performance evaluation by a hesitant fuzzy linguistic best worst method with inconsistency repairing. Journal of Cleaner Production, 232: 657-671.
  • Ozkan, B., Ozceylan, E., Kabak, M. Dagdeviren, M. 2020. Evaluating the websites of academic departments through SEO criteria: a hesitant fuzzy linguistic MCDM approach. Artificial Intelligence Review, 53: 875-905.
  • Boyaci, A. C. 2020. Selection of eco-friendly cities in Turkey via a hybrid hesitant fuzzy decision making approach. Applied Soft Computing, 89: 106090.
  • Hai, W., Xu, Z. S., Zeng, X. J. 2018. Hesitant fuzzy linguistic term sets for linguistic decision making: Current developments, issues and challenges. Information Fusion, 43: 1-12.
  • Liao, H. C., Xu, Z. S., Herrera-Viedma, E., Herrera, F. 2018. Hesitant fuzzy linguistic term set and its application in decision making: a state-of-the-art survey. International Journal of Fuzzy Systems, 20: 2084-2110.

Hesitant Fuzzy Linguistic Decision Making Approach for Stroller Selection

Yıl 2021, Cilt: 10 Sayı: 4, 1464 - 1473, 31.12.2021
https://doi.org/10.17798/bitlisfen.960814

Öz

Having a baby brings new changes and challenges in parents’ life. There is a list of things which are required in order to provide a comfortable life for the baby. Since most of the people have limited economic resources, determination of the things to be bought becomes an important decision for parents. Moreover, the number of alternatives for the items in shopping list (bed, clothes, feeding equipment, stroller, etc.) is very much. Therefore, making a choice among alternative items is necessary. For each item, different alternatives have several advantages over another in views of different aspects. Consideration of several aspects of items would lead to good decisions, and parents must evaluate things in this way. It is aimed in this research to develop an analytic decision-making approach for stroller selection decision of parents. Hesitant fuzzy linguistic terms set (HFLTS) approach was presented in order to model the uncertain situations that the decision makers feel hesitant over various values of a linguistic variable. By using this pattern, elicitation of linguistic information is improved and thoughts of decision makers are represented better in decision models. Under the consideration of hesitant feelings of parents, HFLTS based group decision making approach is utilized to determine the optimum stroller. Apracticeof the presented model is presented to indicate its applicability and the presented decision approach seems useful for stroller selection.

Kaynakça

  • Zadeh, L. A. 1965. Fuzzy sets. Information and Control, 8: 338-&.
  • Bellman R. E., Zadeh, L. A. 1970. Decision-making in a fuzzy environment. Management Science Series B-Application, 17: B141-B164.
  • Zadeh, L. A. 1975. Concept of a linguistic variable and ıts application to approximate reasoning-1. Information Sciences, 8: 199-249.
  • Atanassov, K. T. 1986. Intuitionistic fuzzy-sets. Fuzzy Sets and Systems, 20: 87-96.
  • Smaradache, F. 2002. A unifying field in logics: neutrosophic logic. Multiple-Valued Logic, 8: 385–438.
  • Torra, V. 2010. Hesitant fuzzy sets. International Journal of Intelligent Systems, 25: 529-539.
  • Rodriguez, R. M., Martinez, L. Herrera, F. 2012. Hesitant fuzzy linguistic term sets for decision making. IEEE Transactions on Fuzzy Systems, 20: 109-119.
  • Yavuz, M., Oztaysi, B., Onar, S. C., Kahraman, C. 2015. Multi-criteria evaluation of alternative fuel vehicles via a hierarchical hesitant fuzzy linguistic model. Expert Systems with Applications, 42: 2835–2848.
  • Wang, J., Wang J. Q., Zhang, H. Y. 2016. A likelihood-based TODIM approach based on multi hesitant fuzzy linguistic information for evaluation in logistics outsourcing. Computers & Industrial Engineering, 99: 287-299.
  • Sun, R. X., Hu, J. H., Zhou J. D., Chen, X. H. 2018. A hesitant fuzzy linguistic projection based mabac method for patients' prioritization. International Journal of Fuzzy Systems, 20: 2144-2160.
  • Wu, Z. B., Xu, J. P., Jiang X. L., Zhong, L. 2019. Two MAGDM models based on hesitant fuzzy linguistic term sets with possibility distributions: VIKOR and TOPSIS. Information Sciences, 473: 101-120.
  • Ji, P., Zhang H. Y., Wang, J. Q. 2018. A projection-based outranking method with multi hesitant fuzzy linguistic term sets for hotel location selection. Cognitive Computation, 10: 737-751.
  • Liao, H. C., Wu, X. L., Liang, X. D., Xu, J. P., Herrera, F. 2018. A new hesitant fuzzy linguistic ORESTE method for hybrid multicriteria decision making. IEEE Transactions on Fuzzy Systems, 26: 3793-3807, 2018.
  • Xue, Y. X., You, J. X., Zhao X. F., Liu, H. C. 2016. An integrated linguistic MCDM approach for robot evaluation and selection with incomplete weight information. International Journal of Production Research, 54: 5452-5467.
  • Wu, Y. N., Wang, Y., Chen, K. F., Xu C. B., Li, L. W. Y. 2017. Social sustainability assessment of small hydropower with hesitant PROMETHEE method. Sustainable Cities and Society, 35: 522-537.
  • Wu Y. N., Zhou, J. L. 2019. Risk assessment of urban rooftop distributed PV in energy performance contracting (EPC) projects: An extended HFLTS-DEMATEL fuzzy synthetic evaluation analysis. Sustainable Cities and Society, 47: 101524.
  • Liao, H. C., Mi, X. M., Yu Q., Luo, L. 2019. Hospital performance evaluation by a hesitant fuzzy linguistic best worst method with inconsistency repairing. Journal of Cleaner Production, 232: 657-671.
  • Ozkan, B., Ozceylan, E., Kabak, M. Dagdeviren, M. 2020. Evaluating the websites of academic departments through SEO criteria: a hesitant fuzzy linguistic MCDM approach. Artificial Intelligence Review, 53: 875-905.
  • Boyaci, A. C. 2020. Selection of eco-friendly cities in Turkey via a hybrid hesitant fuzzy decision making approach. Applied Soft Computing, 89: 106090.
  • Hai, W., Xu, Z. S., Zeng, X. J. 2018. Hesitant fuzzy linguistic term sets for linguistic decision making: Current developments, issues and challenges. Information Fusion, 43: 1-12.
  • Liao, H. C., Xu, Z. S., Herrera-Viedma, E., Herrera, F. 2018. Hesitant fuzzy linguistic term set and its application in decision making: a state-of-the-art survey. International Journal of Fuzzy Systems, 20: 2084-2110.
Toplam 21 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik
Bölüm Araştırma Makalesi
Yazarlar

Billur Ecer 0000-0001-9692-1450

Yayımlanma Tarihi 31 Aralık 2021
Gönderilme Tarihi 1 Temmuz 2021
Kabul Tarihi 25 Ağustos 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 10 Sayı: 4

Kaynak Göster

IEEE B. Ecer, “Hesitant Fuzzy Linguistic Decision Making Approach for Stroller Selection”, Bitlis Eren Üniversitesi Fen Bilimleri Dergisi, c. 10, sy. 4, ss. 1464–1473, 2021, doi: 10.17798/bitlisfen.960814.



Bitlis Eren Üniversitesi
Fen Bilimleri Dergisi Editörlüğü

Bitlis Eren Üniversitesi Lisansüstü Eğitim Enstitüsü        
Beş Minare Mah. Ahmet Eren Bulvarı, Merkez Kampüs, 13000 BİTLİS        
E-posta: fbe@beu.edu.tr