EconPapers    
Economics at your fingertips  
 

Identifying Relative Marginal Value Functions for Ranking

Majid Mohammadi () and Jafar Rezaei
Additional contact information
Majid Mohammadi: Vrije Universiteit Amsterdam
Jafar Rezaei: Delft University of Technology

A chapter in Advances in Best-Worst Method, 2023, pp 41-47 from Springer

Abstract: Abstract The current multi-criteria decision-making (MCDM) ranking methods provide suggestions on the superiority of an alternative to other alternatives mainly based on the alternatives’ performance difference and the weights (relative importance) of the criteria as absolute values, while the aim of the MCDM is to only provide the relative importance of criteria/alternatives for the decision under study. In this paper, we put forward a way for ranking alternatives with respect to multiple criteria that considers only the relative importance of every pair of criteria/alternatives and provides a ranking that is agnostic to the alternative performance normalization and prevents the rank reversal phenomenon. We apply the proposed procedure to an example to show its inner mechanism.

Keywords: Ranking; Normalization-agnostic; Relative marginal utility (search for similar items in EconPapers)
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:lnopch:978-3-031-24816-0_4

Ordering information: This item can be ordered from
http://www.springer.com/9783031248160

DOI: 10.1007/978-3-031-24816-0_4

Access Statistics for this chapter

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

 
Page updated 2025-04-01
Handle: RePEc:spr:lnopch:978-3-031-24816-0_4