EconPapers    
Economics at your fingertips  
 

Linear Diophantine Fuzzy Information Aggregation with Multi-criteria Decision-Making

H. M. A. Farid and Muhammad Riaz ()
Additional contact information
H. M. A. Farid: University of the Punjab, Department of Mathematics
Muhammad Riaz: University of the Punjab, Department of Mathematics

Chapter Chapter 14 in Fuzzy Optimization, Decision-making and Operations Research, 2023, pp 281-317 from Springer

Abstract: Abstract Linear Diophantine fuzzy set (LDFS) is the integral part of decision-making process under uncertain environment, because of its amazing quality of having a vast portrayal zone for authorized doublets, and the LDFS theory expands the region of fuzzy information that may be obtained by using reference parameters. Because the real world is not accurate, and there is a lack of knowledge, assessing and picking the best option can be a challenging and unexpectedly difficult decision-making issue. The primary goal is to guide decision-makers through the process of selecting the best option inside a linear-Diophantine fuzzy context. We suggested four new aggregation operators (AOs): the “linear Diophantine fuzzy weighted average (LDFWA) operator, linear Diophantine fuzzy ordered weighted average (LDFOWA) operator, linear Diophantine fuzzy weighted geometric (LDFWG) operator, and linear Diophantine fuzzy ordered weighted geometric (LDFOWG) operator.” Following that, the proposed model is validated using a clear example of linear Diophantine fuzzy content. This demonstrates the utility and applicability of the suggested strategy.

Date: 2023
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-35668-1_14

Ordering information: This item can be ordered from
http://www.springer.com/9783031356681

DOI: 10.1007/978-3-031-35668-1_14

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2026-06-25
Handle: RePEc:spr:sprchp:978-3-031-35668-1_14