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Dergiler / Gazi University Journal of Science / 2021 / Cilt: 34 - Sayı: 2

Selecting the Best Normalization Technique for ROV Method: Towards a Real Life Application

Nazlı ERSOY
Sayfa
592–609
Yayın Tarihi
2021-06-01
DOI
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Yapay Zeka Hızlı Bakış & Çıkarımlar

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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Another importance of this study is the first testing the suitability of different normalization techniques for the ROV method.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Normalization is one of the stages that have an impact on the results of MCDM problems.
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Temel Bulgular & Veri:Choosing the right normalization technique leads the decision maker to the right results.
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Sonuç & Katkı:Another importance of this study is the first testing the suitability of different normalization techniques for the ROV method.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:MCDM · Range of Value (ROV) method · Normalization

Abstract

Normalization is one of the stages that have an impact on the results of MCDM problems. Choosing the right normalization technique leads the decision maker to the right results. Accordingly, the purpose of this study is to determine the most appropriate normalization technique for the ROV method. In this study, a real case is analyzed, eight different normalization methods are compared with each other on the basis of a multi-stage framework. The findings show that the model used in this study can be successfully applied in the selection of normalization technique. This study provides a decision support and reference for the selection of nomalization technique for MCDM methods in terms of the framework used. Another importance of this study is the first testing the suitability of different normalization techniques for the ROV method.

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Bu Makaleye Atıf Yap

ERSOY, N. (2021). Selecting the Best Normalization Technique for ROV Method: Towards a Real Life Application. Gazi University Journal of Science, Cilt: 34 - Sayı: 2, 592–609. https://ajindex.com/articles/254367

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Kaynakça (14)

  1. Jahan, A., Edwards, K.L., “A state-of-the-art survey on the influence of normalization techniques in ranking: improving the materials selection process in engineering design”, Materials & Design, 65:335–342, (2015).
  2. Vafaei, N., Ribeiro, R. A., Camarinha-Matos, L. M., “Selecting Normalization Techniques for the Analytical Hierarchy Process”, Doctoral Conference on Computing, Electrical and Industrial Systems, 43-52, (2020).
  3. Pavlicic, D., “Normalization affects the results of MADM methods”, Yugoslav Journal of Operations Research, 11(2):251–265, (2001).
  4. Milani, A.S., Shanian, R., Madoliat, R. and Nemes, J.A., “The effect of normalization norms in multiple attribute decision making models: a case study in gear material selection”, Structural and Multidisciplinary Optimization, 29(4):312–318, (2005).
  5. Zavadskas, E.K., Zakarevicius, A., Antucheviciene, J., “Evaluation of ranking accuracy in multi-criteria decisions”, Informatica, 17(4):601–617, (2006).
  6. Lai, Y. J., Hwang, C. L. “Fuzzy multiple objective decision making: Methods and Applications”. Berlin: Springer-Verlag, (1994).
  7. Brauers, W.K., Zavadskas, E.K., “The MOORA method and its application to privatization in a transition economy”, Control and Cybernetics, 35(2):443–468, (2006).
  8. Mathew, M., Sahu, S., Upadhyay, A. K., “Effect Of Normalization Techniques In Robot Selection Using Weighted Aggregated Sum Product Assessment,” Int. J. Innov. Res. Adv. Stud., 4(2):59-63, (2017).
  9. Chakraborty, S. and Yeh, C. H., “A simulation based comparative study of normalization procedures in multiattribute decision making”, 6th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases, Corfu Island, Greece, 102-109, (2007).
  10. Chakraborty, S.,Yeh, C-H., “A simulation comparison of normalization procedures for TOPSIS’, Computing Industrial Engineering, 5(9):1815–1820, (2009).
  11. Celen, A., “Comparative analysis of normalization procedures in TOPSIS method: with an application to Turkish deposit banking market”, Informatica, 25(2):185-208, (2014).
  12. Shannon, C.E., “A Mathematical Theory Of Communication”, Bell System Technical Journal, 27:379-423, (1948).
  13. Wu, Z., Sun, J., Liang, L., Zha, Y., “Determination of Weights For Ultimate Cross Efficiency Using Shannon Entropy”, Expert Systems With Applications, 38:5162–5165, (2011).
  14. Wang, T. C., Lee, H. D., “Developing a fuzzy TOPSIS approach based on subjective weights and objective weights”, Expert systems with applications, 36(5):8980-8985, (2009). Yako