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Treatment of the Multi-Attribute Decision-Making Rank Reversal Problem for Real-World Systems

Authors:
Steve Chan

Keywords: decision engineering pathway; decision-making; multi-criteria decision-making; multi-attribute decision-making; rank reversal; multi-objective decision-making; decision quality; artificial intelligence; machine learning; epistemic transparency.

Abstract:
This paper describes an enhanced approach towards considering the Rank Reversal (RR) problem for certain Multi-Attribute Decision-Making (MADM) methods critical to Multi-Criteria Decision-Making (MCDM) systems. Prototypical testing environments for RR usually do not include key facets of Real-World Systems (RWS), such as the treatment of time, prospective Influence Dominating Sets (IDS) at play, sub-biases throughout the system, involved Decision Engineering Pathways (DEP) for consortial environments, and a more Transparent, Explainable, and Accountable (TEA)- oriented architectural construct, which are all desired in these contemporary times. These facets have been considered as Extrapolated Decision Quality (DQ) Thematics (EDQTs) of the Howard & Abbas six classically understood facets of DQ, and they are critical for MCDM RWS. Since various MADM methods vary in performance against the EDQTs, the approach utilized is to employ a robust Multi-Objective Decision-Making (MODM) module to discern the more optimal MADM methods to utilize in an ongoing fashion.

Pages: 1 to 10

Copyright: Copyright (c) IARIA, 2025

Publication date: April 6, 2025

Published in: conference

ISSN: 2308-3735

ISBN: 978-1-68558-259-3

Location: Valencia, Spain

Dates: from April 6, 2025 to April 10, 2025