Journals / Ege Akademik Bakış / 2014 / Cilt: 14 - Sayı: 2

The effects of the normalization methods to multi criteria decision making process– moora method review

Normalizasyon yöntemlerinin çok ölçütlü karar verme sürecine etkisi–moora yöntemi incelemesi

Pages
283–294
Publication Date
2022-10-12
DOI
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AI Summary & Key Takeaways

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

Then, the preference rankings have been analysed for Moora multi criteria decision making method by applying different normalization methods for the data sets.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Companies have to make a choice among alternatives by taking into consideration many different evaluation criteria together.
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Key Findings & Data:In real world, same measurement units of the evaluation criteria are impossible.
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Conclusion & Impact:Then, the preference rankings have been analysed for Moora multi criteria decision making method by applying different normalization methods for the data sets.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

Companies have to make a choice among alternatives by taking into consideration many different evaluation criteria together. In real world, same measurement units of the evaluation criteria are impossible. The methods used for analysing the evaluation criteria which have got different measurement units are called multi criteria decision making methods. There have been different normalization methods used for analysing the evaluation criteria which have got different measurement units in the multi criteria decision making methods. The different multi criteria decision making methods have used different normalization methods. Moreover, the different normalization methods can be used in the same multi criteria decision making method. The purpose of this study is to analyse the effects of the different normalization methods in the decision. For this purpose, the data sets have been derived. Then, the preference rankings have been analysed for Moora multi criteria decision making method by applying different normalization methods for the data sets.

Özet

İşletmeler çok sayıda değerlendirme ölçütünü bir arada gözönüne alarak alternatifler arasında seçim yapmak durumundadırlar. Bu değerlendirme ölçütlerinin ölçüm birimlerinin aynı olması durumu ise gerçek hayatta hemen hemen imkansızdır. Ölçüm birimleri farklı olan ölçütleri birarada incelemek için kullanılan yöntemler çok ölçütlü karar verme yöntemleri adıyla anılmaktadır. Çok ölçütlü karar verme yöntemlerinde ölçüm birimleri farklı olan ölçütleri incelemek için kullanılan çeşitli normalizasyon yöntemleri mevcuttur. Farklı çok ölçütlü karar verme yöntemleri farklı normalizasyon yöntemleri kullanmakta hatta aynı yöntem için literatürde farklı normalizasyon yöntemlerinin kullanıldığı bile görülmektedir. Bu çalışmanın amacı farklı normalizasyon yöntemlerinin alınan kararda bir değişiklik yaratıp yaratmadığını incelemektir. Bu amaçla veri setleri türetilerek Moora çok ölçütlü karar verme yöntemi için farklı normalizasyon yöntemleri uygulanmış ve tercih sırasının değişip değişmediği incelenmiştir.

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Cite This Article

ÖZDAĞOĞLU, A. (2022). The effects of the normalization methods to multi criteria decision making process– moora method review. Ege Akademik Bakış, Cilt: 14 - Sayı: 2, 283–294. https://ajindex.com/articles/495361

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References (12)

  1. Aalami, H.A., Moghaddam, M.P. ve Yousefi, G.R. (2010) “Modeling and Prioritizing Demand Response Programs in Power Markets” Electric Power Systems Research, 80: 426–435.
  2. Ayala, J.G. (2012) “Selecting Irrigation Water Pricing Alternatives Using A Multi-Methodological Approach” Mathematical and Computer Modelling, 55: 861–883.
  3. Balezentis, A. Balezentis, T. ve Brauers, W.K.M. (2012) “Personnel Selection Based on Computing with Words and Fuzzy MULTIMOORA” Expert Systems with Applications, 39: 7961–7967.
  4. Brauers, W.K.M. ve Zavadskas, E.K. (2009) “Robustness of The Multi-Objective MOORA Method with A Test for The Facilities Sector” Technological and Economic Development of Economy: Baltic J on Sustainability, 15: 352-375.
  5. Chakraborty, S. (2011) “Applications of The MOO- RA Method for Decision Making in Manufacturing Environment” Int J Adv Manuf Technol, 54: 1155–1166.
  6. Chatterjee, P., Athawale, V.M. ve Chakraborty, S. (2011) “Materials Selection Using Complex Proportional Assessment and Evaluation of Mixed Data Methods” Materials and Design, 32: 851–860.
  7. Chatterjee, P. ve Chakraborty, S. (2012) “Material Selection Using Preferential Ranking Methods” Materials and Design, 35: 384–393.
  8. Dai, L. ve Wang, J. (2011) “Evaluation of The Profitability of Power Listed Companies Based on Entropy Improved TOPSIS Method” Procedia Engineering, 15: 4728 – 4732. Das, M.C., Sarkar, B. ve Ray, S. (2012) “A Framework To Measure Relative Performance of Indian Technical Institutions Using Integrated Fuzzy AHP and COPRAS Methodology” Socio-Economic Planning Sciences, 1-12. (Baskıda makale). Huang, W. ve Huang, Y.Y. (2012) “Research on The Performance Evaluation of Chongqing Electric Power Supply Bureaus Based on TOPSIS” Energy Procedia, 14: 899 – 905. Kaklauskas, A., Zavadskas, E.K., Naimaviciene, J., Krutinis, M., Plakys, V. ve Venskus, D. (2010) “Model for A Complex Analysis of Intelligent Built Environment” Automation in Construction, 19: 326–340.
  9. Kaklauskas, A., Zavadskas, E.K. ve Trinkunas, V. (2007) “A Multiple Criteria Decision Support On-Line System for Construction” Engineering Applications of Artificial Intelligence, 20:163–175.
  10. Kalaycı, Ş. (2010) SPSS Uygulamalı Çok Değişkenli İstatistik Teknikleri, Ankara,
  11. Asil Yayın Dağıtım. Karande, P. ve Chakraborty, S. (2012) “Application of Multi-Objective Optimization on The Basis of Ratio Analysis (MOORA) Method for Materials Selection” Materials and Design, 37: 317–324
  12. Kiran, C.P., Clement, S. ve Agrawal, V.P. (2011) “Coding, Evalu