An output-oriented classification of multiple attribute decision-making techniques based on fuzzy c -means clustering method

Ezzatollah Asgharizadeh, Mohammadreza Taghizadeh Yazdi, Abdolkarim Mohammadi Balani
  • International Transactions in Operational Research, August 2017, Wiley
  • DOI: 10.1111/itor.12449

grouping multiple attribute decision-making techniques (MADM)

What is it about?

Multiple attribute decision-making (MADM) techniques lack a comprehensive classification. We measure the performance of 17 techniques and classify them into some groups based on their performance using fuzzy c-means clustering method.

Why is it important?

-- We measured the quantitative performance of MADM techniques in 7 variables (simplicity in learning and deploying, speed, complexity of calculations, the number of inputs, the quality of the underlying logic, the quality of rankings, and the rate of growth in large problems). -- We presented for the first time a classification approach that considers the performance of MADM technique, that's why we call it output-oriented. Previous works had only provided input-oriented or process-oriented classifications.


Dr Mohammad Reza Taghizadeh Yazdi
University of Tehran

I hope this article provide a new idea for the classifications and comparisons to be suggested in future

Read Publication

The following have contributed to this page: Dr Mohammad Reza Taghizadeh Yazdi and Mr. Abdolkarim Mohammadi-Balani