An Integrated CODAS Method and Novel Surface-based Weighted Distance Measures under Neutrosophic Environment

Abstract

Information theory provides suitable tools for solving practical problems, particularly 
multi-criteria decision-making (MCDM) problems under neutrosophic environments. Generally, a 
wide range of MCDM solution methods are constructed based on distance measures category. The 
defined distance measures for continuous neutrosophic numbers, especially its trapezoidal type, is 
very limited rather than discrete type. The main goals of this study is to come up with a way to add 
two new types of weighted distance measures based on meaningful surfaces: Euclidean and 
Hamming. To define these measures, all three components of the neutrosophic trapezoidal fuzzy 
number (truth, indeterminacy, and falsity membership functions) have been used simultaneously. 
The proof of some theorems and properties for the weighted distance measures demonstrates their 
validity. The CODAS algorithm is known as one of the distance-based methods for solving MCDM 
problems. The following represents the CODAS algorithm based on two novel distance measures. In 
addition, an explanatory example from the research literature is given to check the performance of 
the proposed hybrid algorithm. The results of this study indicate that the algorithm based on the 
proposed measures obtains a reasonable and appropriate ranking order between the options. 
Furthermore, the sensitivity parameter analysis and comparative analysis show the flexibility and 
accuracy of the suggested measures in the combined algorithm. The acceptable efficiency of proposed 
distance measures formed on the surfaces can shed light on research related to distance measures in 
the methodology and implicated aspects.

DOI: 10.5281/zenodo.11479254