Fuzzy Analytic Hierarchy Process (Fuzzy AHP) – With Example

The Fuzzy Analytic Hierarchy Process, often abbreviated as Fuzzy AHP, is a robust decision-making method that introduces a layer of fuzziness to the traditional Analytic Hierarchy Process (AHP). This enhancement allows decision-makers to handle imprecise or uncertain data, making it a valuable tool in situations where clarity may be lacking. In essence, Fuzzy AHP extends

Fuzzy TOPSIS Method with a Simple Example

Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) is a decision-making method used in multi-criteria analysis to evaluate and rank alternatives when dealing with uncertain or imprecise information. Developed by Hwang and Yoon in 1981, Fuzzy TOPSIS has found applications in various fields, including engineering, finance, environmental management, and more.

ANP Method or Analytical Network Process with a Simple Example

The abbreviation ANP stands for “Analytical Network Process,” a method used for network analysis. ANP is a decision-making technique that shares significant similarities with the Analytic Hierarchy Process (AHP). The ANP method, introduced by Thomas L. Saaty, aims to select appropriate options based on multiple criteria. It is also employed for weighting criteria and sub-criteria.

Analytical Hierarchy Process (AHP): Step-by-step example

In this article, we are going to solve a practical example step-by-step using the Analytic Hierarchy Process (AHP). Before we proceed, let us provide an introduction to AHP and explain why it is necessary. Introduction to Analytic Hierarchy Process (AHP) Multi-criteria decision making (MCDM) is a decision-making approach that allows experts to take into account