qR-MARCOS - q-Rung Orthopair extension of MARCOS

Overview

QR-MARCOS reads every cell as a q-rung orthopair pair (mu, nu). Cost criteria are replaced by their complement, each cell becomes a score S = (1 + mu^q - nu^q)/2 in [0, 1], and the MARCOS utility ladder runs on the weighted score matrix. This is a derived construction: no accessible published q-ROF MARCOS worked example exists, so the cell handling follows Yager 2017 and Wang 2020 while the ladder follows the open-access crisp MARCOS formulation of Ismail et al. 2026.

Output

utility, higher is better

Data

Q-Rung Orthopair Fuzzy, uncertainty tuples complete

Weights

Needs a weight source

Size

2+ alternatives, 3-10 criteria works best

Used for

Q-Rung Orthopair Fuzzy MCDM, MAGDM under epistemic uncertainty, expert-driven evaluation with linguistic terms

Look elsewhere when

Assumptions to verify

• Decision matrix entries are valid q-Rung Orthopair Fuzzy numbers/tuples
• Underlying crisp method's compensation assumption holds in uncertain space
• All decision-maker(s) and experts use the same linguistic/uncertainty scale

Edge cases and pitfalls

• Value-space violation: ensure all entries satisfy q-ROFN: μ^q + ν^q ≤ 1, q ≥ 1 (q=1→IFS; q=2→PFS) before computation.

• The score function fixes how a cell is read: S = (1 + mu^q - nu^q)/2 stays in [0, 1], which the MARCOS utility ratios need; a score that can turn negative breaks them.

Works with

How to cite